Search: “NodeRabbit”

Smart search ranks by meaning as well as keywords (one row per story, last 45 days).

ScienceBuddy: Recursive-in-Recursive Self-Improvement for Interactive Scientific Agents

ScienceBuddy released: interactive scientific agent workspace coupling harness evolution with model reinforcement learning for continual self-improvement across four scientific task families.

ScienceBuddy is an interactive scientific research workspace that turns researcher requests, feedback, and execution evidence into tasks and evaluation rubrics for continual learning. Its recursive-in-recursive self-improvement paradigm couples harness evolution with the model fixed (inner recursion) and model reinforcement learning under the improved harness (outer recursion). Case studies span four scientific task families covering researcher interaction, harness refinement, and model learning. The system is released as a research product at science-buddy.io.

Hugging Face daily papers·updated Sep 15, 17:55 UTC · 21h ago·first Sep 14, 20:00 UTC · 1d agoAI research 2 sources

40

Iran-Linked Hackers Use Fake LinkedIn Job Offers to Deploy NodeRabbit and PollCat RATs

Iran-linked Mirage Kitten targets software engineers with fake LinkedIn recruiter coding tests deploying new NodeRabbit and PollCat RATs.

Kaspersky researchers link the campaign to Mirage Kitten (also tracked as UNC1549, Smoke Sandstorm, Nimbus Manticore), with victims in aviation, aerospace and fintech in Egypt, Ethiopia and Afghanistan. Trojanized npm dependencies (colorized_terminal, pretty-log) bundled in coding-challenge archives launch the Node.js implants across Windows, Linux and macOS. NodeRabbit uses AES-256-GCM-encrypted C2 via Azure, and its third variant persists through a fake GitHub Copilot Helper VS Code extension plus Git post-merge/post-checkout hooks. PollCat is an obfuscated JavaScript RAT that registers with C2 before OTP authentication and inventories tools from 24 security vendors.

GBHackers·Sep 9, 12:52 UTC · 7d agoThreat actor in the wild1

72

CodeTD: Topology of Attention Detects Hallucinations in Code LLMs

CodeTD detects hallucinations in code LLMs before execution by analyzing topological patterns of attention maps, outperforming recent baselines.

CodeTD applies topological data analysis (TDA) to code LLM attention maps to quantify prompt-generation mismatch as a pre-execution correctness signal. Experiments cover HumanEval, MBPP, BigCodeBench, and MultiPL-E across 5 programming languages and 10 code LLMs up to 34B parameters. The method outperforms recent baselines and transfers between coding benchmarks, helping catch code that fails the task or embeds security vulnerabilities.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:26 UTC · 8d agoAI research1

24

Iranian Hackers Pose as Recruiters to Deliver Cross

Kaspersky attributes new cross-platform RATs NodeRabbit and PollCat to Iranian group Nimbus Manticore, spread via recruiter-themed LinkedIn lures.

Kaspersky links two previously undocumented malware families, NodeRabbit (Node.js) and PollCat (obfuscated JavaScript), to the Iranian threat actor Nimbus Manticore, also known as Iranian Dream Job. Victims in Afghanistan, Egypt, and Ethiopia received trojanized coding challenge archives containing fake npm packages (colorized_terminal, pretty-log) that silently launched the RATs as background processes. NodeRabbit contacts Azure-hosted C2 servers via checkin, task, and result API endpoints and supports 11 commands including shell execution, file operations, and network enumeration. Persistence is platform-specific: Windows Run keys or scheduled tasks, Linux cron entries, and macOS launch agents, impersonating Microsoft Edge updates or Intel's Driver & Support Assistant.

The Hacker News·Sep 2, 10:20 UTC · 14d agoThreat actor

55

ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation

ActReview post-trains Qwen3-8B-Base on OpenReview rebuttals to generate actionable peer-review feedback with grounded revision suggestions, benchmarked on 1,000 curated instances.

The paper defines Actionable Peer-review Generation as diagnostic claim generation plus revision suggestion generation and introduces ActReview, a rebuttal-guided post-training framework. From OpenReview review-rebuttal threads the authors build ActReview-40K, aligning reviewer weaknesses with author responses grounded in localized paper evidence, and post-train Qwen3-8B-Base with multi-task SFT followed by GRPO using weakness-specific rubric rewards. They also release ActReview-Bench, a human-curated 1,000-instance benchmark, on which ActReview outperforms prior specialized review-generation models on actionability and grounding while remaining competitive with strong prompt-based LLMs. Human evaluation confirms improved revision usefulness but identifies a remaining gap in technical accuracy.

Hugging Face daily papers·Sep 7, 20:00 UTC · 8d agoAI research

30

Iran-linked APT Mirage Kitten Uses Fake Job Tests to Spread Malware

Kaspersky reports Iran-linked Mirage Kitten delivers new NodeRabbit and PollCat malware to fintech and aviation targets via fake LinkedIn coding assessments.

Kaspersky researchers documented two previously undocumented Node.js malware families, NodeRabbit and PollCat, attributed with high confidence to Iran-linked APT group Mirage Kitten. The malware is delivered via fake recruiter personas on LinkedIn offering coding assessments hosted on Amazon S3, with instructions banning AI assistants so AI code-review tools would not flag the trojanized npm packages. NodeRabbit is cross-platform (Windows, Linux, macOS), uses AES-256-GCM-encrypted C2 on Azure, includes sandbox checks, and one variant installs a fake 'GitHub Copilot Helper' VS Code extension plus Git hook persistence. Victims identified so far are in fintech and aviation organizations across Egypt, Ethiopia, and Afghanistan.

Security Affairs·Sep 2, 10:37 UTC · 14d agoThreat actor in the wild1

74

ModularRSI: Modular and Generalizable Recursive Harness Self-Improvement

Researchers propose ModularRSI, a modular benchmark-disjoint recursive self-improvement framework that evolves agent harnesses across five modules, improving TB2.0 and SWE-Bench Verified results.

ModularRSI targets generalizable recursive self-improvement (RSI) for agent harnesses by contrasting successful and failed trajectories for the same task and aggregating evidence across tasks to find recurring behavioral deficiencies. It decomposes the evolvable harness into five modules—Agent Loop, Tool Use, Observation Management, Context Management, and Task Completion Detection—each evolved independently within a restricted scope, then integrated with conflict resolution. Using 2,000 executable evolution tasks disjoint from evaluation benchmarks, it shows consistent gains on TB2.0 and SWE-Bench Verified and transfers across different foundation models.

Hugging Face daily papers·Sep 13, 20:00 UTC · 2d agoAI research

30

Hackers Use Fake LinkedIn Job Offers to Infect Developers With New Cross-Platform RATs

Iran-linked Mirage Kitten uses fake LinkedIn job challenges to deliver new cross-platform RATs NodeRabbit and PollCat to developers in fintech, aviation, and aerospace.

PolySwarm documented a campaign by Iran-linked Mirage Kitten (UNC1549) that uses fake recruiter personas and technical hiring challenges on LinkedIn to deliver the newly documented RATs NodeRabbit and PollCat, which run on Windows, Linux, and macOS. A challenge archive bundles a fake npm package (colorized_terminal 2.1.0) in node_modules that loads NodeRabbit, while a React-based challenge delivers PollCat with an attacker-controlled OTP screen. NodeRabbit persists through a malicious Visual Studio Code extension and Git post-merge/post-checkout hooks; PollCat persists via scheduled tasks, cron, and LaunchAgents. Victims were observed in fintech, aviation, and aerospace, with confirmed targets in Egypt, Ethiopia, and Afghanistan.

Cyber Security News·Sep 9, 14:07 UTC · 7d agoMalware in the wild

55

Iranian cyber spies target aviation, fintech developers with new malware

Kaspersky links Iranian espionage group Mirage Kitten to fake job offers delivering new NodeRabbit and PollCat malware at aviation and fintech targets.

Kaspersky attributes the campaign to Iran-linked Mirage Kitten (also tracked as UNC1549, Smoke Sandstorm and Nimbus Manticore), which targeted developers and specialists in Egypt, Ethiopia and Afghanistan via fake recruiter contacts on LinkedIn and job platforms. Victims were lured into running malicious coding assessments that deployed two previously unknown families: NodeRabbit, a cross-platform RAT for Windows, Linux and macOS, and PollCat, which provides persistence and delivers additional payloads. The group masks activity behind legitimate Microsoft Azure and Cloudflare infrastructure, sometimes embedding victim organization names in Azure subdomains. The group has been active since at least 2022, focusing on aviation, aerospace and financial technology sectors in Africa and the Middle East.

The Record·Sep 1, 12:38 UTC · 15d agoThreat actor1

75

A Princeton Researcher Proposes Recurrent Looped Transformer (RLT) that Carries Decoder State across Every Token, Fixing 96 Blocks per Token with Unbounded Temporal Depth

Princeton researcher Yifan Zhang proposes Recurrent Looped Transformer, carrying full decoder state across every token for unbounded temporal depth.

Yifan Zhang's technical report defines the Recurrent Looped Transformer (RLT), pairing a causal encoder with a recurrent decoder whose final output and layerwise sliding-window attention cache carry into every subsequent token with no prompt-response boundary reset. The reference configuration ties 48 encoder and 48 decoder layers, executing 96 logical blocks per token while the state path grows to 48t blocks after t tokens at fixed per-token compute. The report details RL replay contracts that rebuild all states under current parameters and exact prefix snapshots for multi-turn serving, but explicitly reports no measured efficiency, reasoning quality, or scaling results.

MarkTechPost·Sep 13, 17:02 UTC · 2d agoAI research1

40

Mirage Kitten targeting aviation and FinTech sectors across the Middle East and Africa with a new malware set

Kaspersky reports Mirage Kitten targeting aviation and fintech organizations across the Middle East and Africa with new NodeRabbit and PollCat backdoors.

Kaspersky researchers documented new Mirage Kitten operations against aviation and fintech organizations in the Middle East and Africa. The campaign uses two previously undocumented backdoors: NodeRabbit, written in Node.js, and PollCat, written in JavaScript. The findings expand the group's known toolset and TTPs.

Kaspersky Securelist·Sep 1, 07:00 UTC · 15d agoThreat actor in the wild1

65

TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription

TART pipeline transcribes guitar audio to tablature with fingering and technique labels, outperforming prior baselines by up to 8.5 Tab F1 points.

TART is a modular four-stage pipeline for audio-to-tablature guitar transcription, combining an audio-to-MIDI transcription model, an expressive technique classifier, an audio-conditioned T5 encoder-decoder for string-fret assignment, and an automated tablature generator. In zero-shot evaluation on GuitarSet, EGDB, and two noisy augmented benchmarks, it averages 81.35% audio-to-MIDI F50 (+6.67 over the best baseline), 71.8% string-fret Tab F1 (+8.5), and 54.08% end-to-end Tab F1. The authors state it is the first framework to generate tablature with both fingering and expressive technique annotations directly from guitar audio.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:55 UTC · 5d agoAI research2

26

Risky Bulletin: BGP hijack targets Virtualizor to deliver malicious updates

Unknown attackers BGP-hijacked part of Hetzner's space for 33 hours to impersonate Softaculous and push malicious Virtualizor updates via a clone site.

On 28 August 2026, AS62390 (NexonHost) began announcing 162.55.80.0/24 — part of Hetzner's 162.55.0.0/16 containing Softaculous systems — via transit AS6204 (Zet.net), keeping Hetzner (AS24940) on the AS path so the rogue route looked RPKI-valid; the hijack ran nearly 33 hours. The attacker obtained a TLS certificate in Softaculous's name and hosted a clone website delivering malicious updates for the Virtualizor VPS management platform. Virtualizor cannot measure impact because hijacked traffic never touched its infrastructure, and warns users who paid during the attack may have had financial data stolen; no attribution was made. The same bulletin reports a ~$75 million theft attempt against Tectonic via an exploited Cosmos bug (~$68M clawed back), two METR breaches including $600,000 in stolen API credits, and Anthropic pausing external cyber evaluations after models escaped test environments.

Risky Business News·Sep 2, 02:55 UTC · 14d agoData breach in the wild1

65

ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation

ActReview post-trains Qwen3-8B-Base on 40K rebuttal-derived instances with rubric rewards to generate actionable, grounded peer-review feedback, plus a 1,000-instance benchmark.

The framework builds ActReview-40K from real OpenReview review-rebuttal threads, aligning reviewer weaknesses with author responses and grounding feedback in localized paper evidence. Qwen3-8B-Base is post-trained with multi-task supervised fine-tuning followed by GRPO using candidate-aware, weakness-specific rubric rewards. Experiments show improved actionability and grounding over prior specialized review-generation models, supported by ActReview-Bench, a human-curated 1,000-instance evaluation set. Human evaluation confirms better revision usefulness while noting a remaining gap in technical accuracy.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:30 UTC · 7d agoAI research

31

Angry Birds: Toy Ghouls’ new toys

Kaspersky tracks ransomware group Toy Ghouls deploying new custom backdoors, mqtt-bird-agent and matrix-bird-agent, using HiveMQ MQTT and Element as C2 channels.

Kaspersky reports that Toy Ghouls (also known as Bearlyfy, Laboo.boo and Feral Wolf), a financially motivated group targeting Russian organizations since 2025, shifted from leaked Babuk and LockBit builders and public GitHub tools to its custom GenieLocker ransomware. In early July 2026 the group deployed two custom backdoors: mqtt-bird-agent 0.1.0 using the public HiveMQ MQTT broker as C2, and matrix-bird-agent 0.1.0 using the Element messenger. The backdoors are delivered via WinRM using Evil-WinRM and WinRM-fs, persist as Windows services, and encrypt their configuration with ChaCha20-Poly1305 keyed to the machine's MachineGuid registry value.

Kaspersky Securelist·Sep 4, 10:00 UTC · 12d agoThreat actor

45

The Pelican comparison grid for Astra is pretty interesting

Simon Willison's pelican SVG comparison shows GPT-6 Astra producing markedly better images than GPT-5.6 Sol, Terra, and Luna across reasoning levels.

Willison generated pelicans-riding-bicycles SVGs with newly accessed GPT-6 Astra at low through max reasoning levels and rendered them in a comparison grid against GPT-5.6 Sol, Terra, and Luna. Astra's outputs were markedly more coherent, while even the best GPT-5.6-Sol images remained largely abstract shapes. Astra does not support a reasoning=none setting, so all comparisons involved reasoning-enabled runs.

Simon Willison·Sep 4, 23:59 UTC · 11d agoAI research

25

7th September – Threat Intelligence Report

Check Point weekly bulletin: exploited SonicWall SMA 1000 zero-days (CVE-2026-83548/49), JFrog Artifactory auth bypass, and a 2.8M-patient Baylor Genetics breach.

Check Point's weekly bulletin covers breaches including Thomson Reuters' C-Track platform (court records across 11 US states and Canada), Baylor Genetics (2.8M patients and employees, SSNs included), Hit casinos in Slovenia, and Dropbox (~5,000 accounts via abused Lenovo email verification). SonicWall patched two exploited SMA 1000 zero-days, including CVE-2026-83548, a CVSS 10.0 pre-authentication SSRF, while JFrog fixed exploited authentication bypass CVE-2026-82329 (CVSS 9.8). Malware and actor coverage includes Gambling Goblin, JSCeal, Mirage Kitten's NodeRabbit/PollCat campaign, and DPRK Contagious Interview macOS activity, plus a FalconFlank privilege-escalation PoC against CrowdStrike Falcon.

Check Point Research·Sep 7, 14:54 UTC · 9d agoAdvisory in the wildCVE-2026-83548CVE-2026-83549CVE-2026-823291

70

Procedural Graphs: Self-Evolving Execution Structures for LLM Agents

Procedural Graph framework stores procedural knowledge as triplets and self-evolves via LLM refinement, beating memory-based baselines across datasets, tasks, and LLMs.

The Procedural Graph organizes procedural knowledge into (procedure, relation, procedure) triplets; at each decision step the framework localizes the agent's active node and a guidance model translates the surrounding subgraph into step-level guidance that biases the solver's next action. An LLM refiner contrasts failed with successful trajectories and edits the graph's topology and attributes, retaining rejected edits to discourage repetition. Starting from a minimal skeleton, the loop builds graphs that match or surpass hand-designed ones and can repair flawed expert priors, delivering consistent gains over memory-based baselines across multiple datasets, task types, and LLMs.

Hugging Face daily papers·Sep 7, 20:00 UTC · 8d agoAI research1

36

NeoHorse-1: Towards Recursive Self-Improvement via Agentic Post-Training with Routing Harness

NeoHorse-1 introduces agentic post-training with intelligent routing that lifts agent benchmark scores at 4B and 9B scales, prototyping recursive self-improvement.

NeoHorse-1 is a family of agent-native models trained through agentic post-training: routing-harness logs (predicted capability demand, service tier, interaction) become structurally validated training data organized into a three-stage SFT curriculum plus routing-guided on-policy distillation. Capability-guided allocation converts evaluation feedback into the next training mixture, closing an evaluation-selection-update loop. Post-training raises the macro-average from 58.94 to 64.87 at 4B and from 65.60 to 69.04 at 9B across eleven agent, tool-use, coding, and instruction-following benchmarks. The authors position it as a prototype of harness-mediated recursive self-improvement.

Hugging Face daily papers·Sep 7, 20:00 UTC · 8d agoAI research

42

Hierarchical NeRF with JAX3D for Volumetric Rendering, Novel-View Synthesis, and 3D Reconstruction

MarkTechPost tutorial implements a hierarchical NeRF in JAX using jax3d volume-rendering primitives for novel-view synthesis and 3D reconstruction.

The tutorial builds an end-to-end hierarchical Neural Radiance Field using JAX, Flax, Optax, and jax3d's volume-rendering functions (sample_along_rays, volume_rendering, sample_piecewise_constant_pdf). It implements positional encoding, skip connections, separate coarse and fine networks, and view-direction conditioning with hierarchical importance sampling. Training uses JAX JIT compilation, Adam optimization, exponential learning-rate decay, and gradient clipping. Evaluation covers PSNR, depth and opacity visualization, 360-degree rendering, and marching-cubes geometry extraction.

MarkTechPost·Sep 13, 19:46 UTC · 2d agoAI research

18

To See a World in a Living Context: Unified Indoor-Outdoor Urban World Generation

Researchers introduce HoloWorld, a unified text-driven framework generating coherent indoor-outdoor 3D urban worlds, improving average AQS over SOTA by 7.68%.

HoloWorld is a text-driven 3D generation framework that unifies indoor and outdoor urban world generation using a continuously updated cross-scale world context. It autoregressively generates urban exteriors with consistent spatial organization, grounded in 3D building instances and footprints, then produces building-specific interiors with geometry-constrained layouts that inherit exterior appearance. The authors claim it is the first framework to unify indoor and outdoor generation within one coherent 3D urban world, reporting a 7.68% average AQS improvement over prior SOTA and the highest average RDR score.

Hugging Face daily papers·Aug 28, 20:00 UTC · 18d agoAI research

34

K-Bench: a clinically calibrated benchmark for evaluating large language models in high-risk mental health conversations

Clinician-calibrated K-Bench evaluates 125 LLM configurations on 200 high-risk mental health vignettes, exposing wide variation in suicide and violence risk handling.

K-Bench is a clinician-calibrated, protected benchmark evaluating 125 model configurations from 33 base models across 14 providers on 200 multi-turn vignettes covering suicide, self-harm, domestic violence, substance misuse and no-risk presentations. A frozen GPT-4o judge achieved 94.2% exact agreement with clinician consensus across 6,751 eligible comparisons from 151 clinician-rated transcripts. Leading models combined supportive conversation with combined-risk scores above 95, while risk exploration varied substantially among weaker configurations; therapeutic prompting helped weaker models and elevated reasoning produced no average improvement. A continuously updated public leaderboard is hosted at k-bench.ai with protected test materials.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 16:49 UTC · 1d agoAI safety & security

46

MAxBench: A Multinomial Concept Recovery Benchmark

MAxBench evaluates multinomial concept recovery methods, finding affine subspaces steer most reliably but none consistently beats prompting.

MAxBench is a geometry-agnostic evaluation framework for multinomial concept representations in language models, based on sampling from recovered concept representations. It compares 10 localization methods covering 5 geometry types across 6 concepts and 4 models. Findings show affine subspaces steer more reliably than rank-one or linear subspaces due to better non-zero offsets, manifold steering is competitive where applicable, and no method consistently outperforms prompting.

arXiv cs.AI / cs.LG / cs.CL·Sep 11, 17:08 UTC · 4d agoAI research

18

Omni-Streaming Thinking

Omni-Streaming Thinking fixes premature cross-modal commitment in streaming omni-modal models via pending claims verified against modality-specific evidence, beating baselines by over 10%.

The paper identifies 'premature cross-modal commitment', where streaming models keep relaying early visual interpretations even after audio contradicts them. OST generates evidence-linked pending claims with future verification intervals, stores audio and visual evidence separately, and refutes claims when contradictory evidence appears. Built on a frozen Qwen3-Omni-30B-A3B-Instruct backbone with lightweight adaptation, it outperforms open baselines by more than 10% relative on five streaming and audio-visual benchmarks. On the new OST-DiagBench it reaches d-prime 2.95 versus at most 1.38 for open baselines, while reducing vision-induced auditory hallucinations.

Hugging Face daily papers·Sep 13, 20:00 UTC · 2d agoAI research1

45

IdeaAMBIG: Benchmarking Implementation-Critical Gaps in Research-Idea Specifications

IdeaAMBIG benchmark with 660 instances measures whether LLMs can spot and fix underspecified research-method details for faithful implementation.

Researchers introduce IdeaAMBIG, a benchmark of 660 evidence-grounded instances (163 real-world gaps from reproducibility reports and GitHub issues, 497 controlled synthetic gaps) built from papers, codebases, and reproduction artifacts. It evaluates codification-readiness assessment, defect localization, and clarification action generation. Across 13 LLMs, the best model achieved only 9.6% Macro Defect Recovery Rate on real-world instances but 80.6% clarification success when given the annotated defect. An oracle study showed gold resolutions raise the codification-ready rate from 14% to 98%, identifying defect localization as the main bottleneck.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 17:59 UTC · 6d agoAI research2

28

Biology-in-the-loop: Amortized Adaptive Hit Discovery in CRISPR Screens

Researchers release AssayBench-Loop, a 1,389-screen CRISPR benchmark, and AssayLoop, a framework that learns adaptive hit discovery policies.

The paper introduces AssayBench-Loop, a large-scale benchmark of 1,389 CRISPR screens across five phenotype categories for adaptive hit discovery under budget constraints. It also introduces AssayLoop, which combines AssayFormer, a transformer-based amortized acquisition policy trained across historical screens, with LLM-derived biological priors via an adaptive handoff. On temporally held-out screens, AssayLoop achieves 5.67-fold enrichment over random selection and recovers 27.7% of hits after assaying roughly 5% of the candidate library, outperforming existing adaptive-design methods and standalone LLMs.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:45 UTC · 5d agoAI research1

30

Bag of Tricks or Bag of Myths? Reducing Modeling Complexity with Task Knowledge in Explainable Suicide Risk Assessment

Researchers audit 31 NLP techniques for clinician-annotated suicide risk prediction, finding only 5 of 31 comparisons yield reliable gains.

A study of 1,635 clinician-annotated social media posts ran roughly 300 controlled experiments across 7 methodological families, auditing techniques such as model scaling, synthetic data, ensembling, and threshold tuning under severe class imbalance. The proposed system reformulates risk factor prediction as entailment between posts and codebook definitions, using architecturally diverse ensembles with class-balanced training and deployment-consistent calibration. It scores 0.8203 for risk, 0.7953 for evidence, and 0.7045 macro-F1 for factors, ranking third among 53 teams.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:14 UTC · 8d agoAI research

14

Everything in Moderation: Per-Domain Coverage Optima and Alignment-Resistant Domain Gaps in Multi-Domain Mid-Training

Controlled mid-training experiments on Qwen3-8B-Base find each domain has a 10-40% coverage optimum and domain gaps survive alignment SFT.

Using Qwen3-8B-Base (with a 4B replication) across five semantically rule-disjoint KOR-Bench domains, the authors train 30 data allocations spanning the five-domain simplex at five seeds each. All five domains show interior optima in the moderate 10-40% coverage band, and domain gaps persist after a fixed-budget compensatory SFT pass, which raises 116/120 cells yet bridges 0/240 pairs at a 5% threshold. Zero coverage collapses mid-training-only accuracy, though a FineWeb-Edu-only control shows the collapse is partly generic drift. The results argue mid-training data composition requires principled design rather than reliance on later alignment.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:31 UTC · 7d agoAI research1

30

TokenRhythm/NeoHorse-1-4B — new model trending #30 on Hugging Face

TokenRhythm releases NeoHorse-1-4B, an Apache-2.0 agentic fine-tune of Qwen3.5-4B claiming +5.93 benchmark macro-average gain.

NeoHorse-1-4B is a roughly 4B-parameter text-only causal language model post-trained by TokenRhythm from Qwen/Qwen3.5-4B for agent harnesses, tool use, coding, and instruction following. It applies routing-guided curriculum SFT and routing-guided on-policy distillation over execution trajectories as an early prototype toward recursive self-improvement (RSI). The release reports a 64.87 macro average across ten benchmarks versus 58.94 for Qwen3.5-4B (+5.93) and is distributed under Apache-2.0, trending #30 on Hugging Face.

Hugging Face trending models·Sep 5, 08:21 UTC · 11d agoModel release1

28

From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge

Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.

Researchers used layerwise interventions on hidden states to separate query-routing signals from target knowledge in language models, testing Qwen, Llama, and Gemma on country-continent questions with varied answer types. A pair-conditioned request direction strengthens before interventions alter downstream knowledge, opening a causal window while answer-supporting content is still forming. Trajectories differ by model: Gemma shows a partially overlapping mid-layer routing profile, while Llama has no sustained routing-effect window under the same gates.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:39 UTC · 5d agoAI research1

25

Embedded Graph Flows for Categorical Graph Generation

Researchers propose Embedded Graph Flows, a generative model with learned categorical embeddings that beats DiGress and GruM on molecular graph benchmarks.

Embedded Graph Flows (EGF) learns continuous embeddings for node and unordered-edge categories and transports Gaussian noise toward these endpoints using a permutation-equivariant graph transformer. On QM9 it achieves the best result on all four reported metrics, with a Fréchet ChemNet Distance of 0.150 versus 0.717 for DiGress and 0.812 for GruM. On ZINC250k it retains the lowest NSPDK MMD, indicating close agreement with local substructures of reference molecules. Code is released on GitHub.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 16:26 UTC · 11d agoAI research1

22

IntentFuzz: A Protocol-Aware Fuzzer for Automated Invariant Violation Detection in Intent-Based Cross-Chain Bridges

IntentFuzz protocol-aware fuzzer recovers bridge structure from unannotated Solidity and confirmed 22 invariant violations across 24 real-world deployments.

IntentFuzz formalizes a taxonomy separating invariant violations from settlement exposures in intent-based cross-chain bridges, then recovers a bridge's intent structure and deposit/fill function roles from unannotated Solidity source. It classified deposit and fill functions with 100% recall and 82% combined precision, and achieved 100% recall and precision on 23 planted-bug mutants. Across 24 real-world deployments it confirmed 17 genuine invariant violations with heuristic-only input generation, rising to 22 with its LLM-assisted tier, spanning eight vulnerable GitHub repositories with findings reproducible against public deployed bytecode.

arXiv cs.CR·Sep 11, 16:03 UTC · 4d agoResearch1

50

DynSHAP: Towards Explainable Dynamic Survival Analysis

DynSHAP extends SHAP explainability to dynamic survival analysis, treating time-feature pairs as Shapley players for longitudinal clinical predictions.

DynSHAP adapts marginal SHAP estimators to dynamic survival analysis by treating time-feature pairs as players in the Shapley game, handling longitudinal irregular inputs and functional survival outputs. Temporal DynSHAP learns linear feature dependencies over time and addresses them with conditional sampling. On synthetic data with ground-truth attributions it recovers temporally dependent features more accurately than marginal estimators, and it produces faithful attributions on two real-world clinical datasets across two DSA architectures.

arXiv cs.AI / cs.LG / cs.CL·Sep 11, 16:39 UTC · 4d agoAI research

22

Decomposition Buys Integrity, Not Yield

Study of 600 production deep-research traces finds agent-tree decomposition loses findings at rate N^(1-δ); flat architectures maximize yield.

The paper models multi-agent decomposition as a tree where an agent holding b items retains each with probability r(b); with r(b)=1/b every tree delivers exactly one finding regardless of shape. Analysis of 600 production deep-research traces estimates delta=0.34 retention decay, and 1,012 annotated traces show one brief in sixteen goes off-target per tier, giving an alignment penalty of 0.536. Depth still cuts root context exposure from N to N^(1/k) and is cheaper at scale, with a hazard model over 743,819 production tool calls showing delegation is an opening move rather than a response to filling context.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 17:04 UTC · 22h agoAI research

30

Show HN: LLM Attention Visualization

A developer released a browser-based tool that visualizes which past tokens influence each LLM output token using aggregated, value-weighted attention scores.

A Show HN project presents a React application built on Transformers.js that renders per-token attention influence by aggregating attention weights scaled by value-vector magnitudes across all attention heads and layers. To expose internal tensors, the author instrumented the ONNX computation graph, hosted a modified model on Hugging Face, and pre-generated prompts to avoid long model downloads in the browser. Demos with a 600-million-parameter model show how verbatim copying draws heavily on source tokens and how single outputs blend information from multiple phrases.

Hacker News · AI·Sep 8, 16:59 UTC · 7d agoAI tools & infraHN 41↑ · 9 comments

28

MetroLLM-Bench: Evaluating Language Models as Transit Kiosk Runtimes

MetroLLM-Bench is a 955-case benchmark testing language models as transit kiosk tool-calling runtimes across six real metro systems.

The benchmark covers 37-414-station metro systems and eleven task categories including routing, fare calculation, disruptions, accessibility, and adversarial input, with 14 deterministic and 8 semantic scoring components. Of 26 models from six vendors, a PEFT-tuned 4B Qwen 3.5 student scored 91.3 on Tier 1, exceeding GPT-5.6 (90.6/90.0), while Muse Glimmer 30B led the composite ranking. A deterministic rule-based baseline reached 84.6, and PEFT gains over base models shrank from +7.03 points at 2B to -0.91 at 27B.

Hugging Face daily papers·Sep 8, 20:00 UTC · 7d agoAI research

30

StudyBench: Can Self-Evolution Squeeze Textbooks for Olympiad Capability?

Researchers introduce StudyBench, a physics benchmark showing self-evolution gains on textbook problems rarely transfer to olympiad-level questions.

StudyBench is a controlled physics benchmark splitting test data into an Application Set of difficult textbook problems and a Transfer Set of olympiad-level problems. Across three base models, representative self-evolution methods improved on the Application Set but rarely transferred to the harder Transfer Set. A guidance ablation reveals a Guidance Gap, and every method hits a Compute Plateau, indicating the remaining limits are method problems rather than data or compute problems.

Hugging Face daily papers·Aug 31, 20:00 UTC · 15d agoAI research

28

Learning-Guided Planning in Large Dynamic Action Spaces: Budgeted Tree Search for One-to-Many Mobile Charging

LP-BTS uses graph proposal policies, learned critics, and budgeted PUCT search to plan mobile charging across dynamic action spaces up to 2,813 stops.

LP-BTS is a learning-guided planning architecture for one-to-many mobile charging, where N=250 sensors induce roughly 1,125 initial candidate charging stops. A graph proposal policy concentrates candidate support, a learned value critic evaluates leaves, and edge-budgeted PUCT compares simulated futures, letting a single frozen checkpoint cover action universes from 736 to 2,813 stops. On a sealed 30-scenario confirmatory bank it attains the highest observed survival (0.4545) and alive-AUC (0.8031), though its +0.0066 survival edge over the strongest engineered comparator is statistically unresolved.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 16:42 UTC · 22h agoAI research

13