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Student photos, bank details stolen by hackers after St James Anglican School in Perth hit by cyber attack

St James Anglican School in Perth reports hackers stole student photos and family bank details in a contained network breach.

St James Anglican School in Perth's north identified unauthorized access to its computer systems in a cyber breach. Hackers stole students' and families' personal information, including photos and bank details. Parents were advised the school immediately contained the incident and secured its systems.

DataBreaches.net · 1d agoData breach

Australia charges two men for TeamPCP supply

Australia charged two Perth men over TeamPCP supply-chain attacks compromising 1,000+ organizations and exposing 500,000+ credentials.

The AFP charged two Perth-based men with a combined 14 offences for their alleged roles in TeamPCP, with payments in cryptocurrency for data intrusion, identity crime, and money laundering. The group's supply-chain attacks targeted developer tools including TanStack, Trivy, and LiteLLM, with downstream victims including the European Commission and GitHub. Investigators estimate the campaign compromised over 1,000 organizations, exposed more than 500,000 credentials, and led to theft of at least 300 GB of data, with remediation costs in the hundreds of millions of dollars. The men could face a combined 82 years if given maximum sentences, though sentences are typically served concurrently.

The Record · 20d agoPolicy & legal

Mercator ↔ Equal Earth

Simon Willison used GPT-6 Astra (medium) in ChatGPT Work to build an animated D3 transition between Mercator and Equal Earth map projections.

Willison built an animated transition between the Mercator and Equal Earth map projections using D3. The tool was generated by GPT-6 Astra (medium) in ChatGPT Work. Equal Earth is a projection recently voted on at the UN. The post is a vibe-coding demonstration rather than a security or major model event.

Simon Willison · 9d agoAI tools & infra1

Two Arrests, One Supply-Chain Attack, and a Lot of Stolen Credentials

AFP charges two men over TeamPCP open-source supply-chain attacks that stole 500,000+ credentials from 1,000+ organizations via four malware families.

Australian police charged two Western Australian men as principal participants in TeamPCP, which allegedly inserted malicious code into open-source software to steal credentials and sensitive data from government, academia, and private sector organizations worldwide. The campaign compromised more than 1,000 organizations, harvested over 500,000 credentials, and exfiltrated at least 300 GB of data, with remediation costs in the hundreds of millions of dollars. Four malware families were deployed: CanisterWorm (cloud token harvesting), SANDCLOCK (AWS and Kubernetes credential theft), Mini Shai-Hulud (self-replicating npm/PyPI worm), and Miasma (credential-harvesting worm variant). Trojanized tools included Trivy, KICS, LiteLLM, and the Telnyx Python SDK, with exfiltration via GitHub repositories tpcp-docs and docs-tpcp.

Security Affairs · 20d agoThreat actor in the wild1

Mathspace discloses data breach affecting over 1 million people

Mathspace disclosed a Metabase breach exposing data of 1,079,819 students, parents, and staff in Australia and New Zealand.

Mathspace confirmed attackers exploited a vulnerability in its self-hosted Metabase reporting system, gaining administrator access without legitimate login and downloading data on over 1 million people (1,079,819 total) in Australia and New Zealand. Access began August 10, data was downloaded August 27, and the theft was confirmed September 3, 2026. No credentials, academic records, or school-account links were exposed, but affected individuals are warned of targeted phishing. The incident joins a broader campaign against Metabase instances, including Trezor's provider ShipMonk, Framework, and Tally, linked to ShinyHunters via extortion emails and leak-site listings.

BleepingComputer · 9d agoData breach in the wild

Risky Bulletin: Two TeamPCP members arrested in Australia

Australian Federal Police arrested two alleged TeamPCP members behind supply-chain worm attacks that stole over 500,000 credentials from compromised open-source libraries.

The AFP arrested alleged TeamPCP leader Ruben Thomson, 21, and Louis Gaebler, 23, near Perth; both were charged and remain in custody. The group inserted a self-spreading credential-stealing worm into open-source projects including Trivy, KICS, LiteLLM, and Telnyx, harvesting more than 500,000 credentials used for network access, ransomware, extortion, and sales. About 78,000 tokens and secrets from nearly 2,200 organizations leaked online last month, and the FBI supported the investigation that began in April.

Risky Business News · 19d agoPolicy & legal in the wild1

27.5KB language-agnostic WebGPU syntax highlighter

A developer released gpu-lexer, a 27.5KB language-agnostic syntax highlighter that uses a tiny WebGPU model to label code tokens in the browser.

gpu-lexer splits source into words, whitespace, and symbols, then a small WebGPU model uses local and whole-file context to assign nine token classes, working on languages never seen in training. On held-out files, 12.57% of token labels differ from Shiki, though this measures agreement with Shiki rather than objective correctness. In benchmarks against Shiki 4.4.3, Prism.js, Highlight.js, Sugar High, and Starry Night, it highlighted 10 concatenated copies of three.min.js (5.56M characters) about 10x faster on an Apple M4 Pro in Chrome 152. The author frames it as an experiment, not a grammar-equivalent highlighter.

Srsly Risky Biz: China's Private Sector Botnets Are Worth Disrupting

DoJ seized domains of Chinese espionage botnet platforms QScan and QTRouter, run by private firm QTFY for MSS and PLA targeting.

The US Department of Justice disrupted QScan, a distributed vulnerability scanning system with nearly a decade of internet scanning data, and QTRouter, a covert communications platform routing traffic through compromised IoT devices, operated by QTFY under Chinese company Nanjing Xinjiuwei Network Technology. FBI and NSA advisories say QTFY customers include China's Ministry of State Security and the People's Liberation Army, targeting federal agencies, the US Senate, hospitals, telecoms and financial institutions. This is the third Chinese state-backed botnet disrupted since December 2023, following the KV botnet (Volt Typhoon) and Raptor Train (Flax Typhoon), and a sister network, JDY, has more than doubled since the KV disruption. Separately, the Qilin ransomware group claimed a breach of the ATF's CALEA system, briefly publishing 6.3 GB of case folders and forensic data.

Risky Business News · 13d agoThreat actor1

Molecular Déjà Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

Audit of 22 frontier models finds widespread verbatim retrieval of published molecular property values, with higher reasoning increasing recall of memorized numbers.

An arXiv audit tests 22 frontier LLMs across 12 molecular regression benchmarks for verbatim retrieval of published values. More than 50% of the LLMs show verbatim retrieval on five datasets, and identical experiments are flagged 89% more often at a high reasoning level than at the lowest one. Suppressing retrieval moves model prediction errors closer together in relative terms, suggesting predictive capability is not determined solely by memorized values.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research1

Two alleged TeamPCP members arrested and charged after months of software supply

Australian Federal Police, with FBI support, arrested two alleged TeamPCP members behind supply-chain attacks that compromised over 1,000 organizations.

The AFP charged two Western Australian men, identified by media as Ruben Ian Thomson (21) and Louis Michael Gaebler (23), with 14 combined offences including unauthorized data modification and dealing in criminal proceeds. TeamPCP is blamed for poisoning open-source software releases including Trivy, LiteLLM, and the mini Shai-Hulud worm campaign, exposing over 500,000 credentials and at least 300 GB of data. Victims included the European Commission and GitHub, with remediation costs estimated in the hundreds of millions of dollars. Researchers from Flare traced one suspect through leaked passwords, a GitHub alias, and a Steam profile.

CyberScoop · 20d agoPolicy & legal1

Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

Hugging Face published a tutorial on training and finetuning multi-vector embedding models using the Sentence Transformers library.

Hugging Face's blog walks through training and finetuning multi-vector embedding models with Sentence Transformers. Multi-vector approaches store multiple vectors per document to support late-interaction retrieval. The post is a practical guide for developers building retrieval pipelines with the library.

Hugging Face Blog · 21d agoAI tools & infra1

Risky Bulletin: Dutch intel services to get extensive new powers

Netherlands proposed a bill granting AIVD and MIVD expanded warrantless tapping, faster hacking powers, and forced data disclosure, citing Russia, China, and Iran threats.

The Dutch government introduced a bill greatly expanding surveillance powers of intelligence agencies AIVD and MIVD, allowing up to one year of tapping without pre-approval and simplified hacking operations against 'foreign adversaries'. Agencies could compel Dutch companies or citizens to provide data under threat of charges, share data with the private sector, and oversight bodies would merge into a new CTT board. The bill follows similar overhauls in Ireland, Germany, and France after Russia's invasion of Ukraine. The newsletter also reports Moonwell hacked for $8.7M, a Cosmos EVM bug exploited for ~$3M, ShinyHunters listing McKesson with claimed hundreds of millions of records, and a pro-Kremlin DDoS claim against Norway's government network.

Risky Business News · 16d agoPolicy & legal

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 · 19d agoAI research

Alleged TeamPCP Hackers Charged in Australia Over Major Supply Chain Attacks

Australian Federal Police charges two men with 14 offences over TeamPCP supply chain backdoors in Trivy, Checkmarx KICS, and LiteLLM affecting 1,000+ organizations.

The Australian Federal Police charged two Western Australian men, aged 21 and 23, with 14 offences for their alleged principal roles in TeamPCP's March 2026 supply chain attacks; they appeared in Perth Magistrates Court on August 27, 2026. The group stole publishing credentials from trusted open-source projects and pushed poisoned releases across five ecosystems - GitHub Actions, Docker Hub, npm, PyPI, and OpenVSX - with LiteLLM's unpinned Trivy install enabling token theft and backdoored LiteLLM releases. The FBI said the malicious code potentially compromised more than 1,000 organizations, enabled theft of over 500,000 credentials, and exfiltrated at least 300 GB of data. Oligo Security linked the group's infrastructure to activity back to 2020, previously tracked as TA-NATALSTATUS and IronErn.

The Hacker News · 20d agoPolicy & legal in the wild1

Mathspace Breach Impacts More Than 1 Million Users in Australia, NZ

Mathspace confirmed a breach affecting 1,079,819 people in Australia and New Zealand after unauthorized parties downloaded user data from an internal system.

Mathspace confirmed on September 3, 2026 that a breach affected 1,079,819 people in Australia and New Zealand. Unauthorized parties accessed an internal reporting system and downloaded user information. Affected records involve students, parents or guardians, teachers, and Mathspace staff, including names and other data.

DataBreaches.net · 9d agoData breach

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

Grouped Value Attention stores grouped values and reconstructs content keys via a learned linear map, cutting KV-cache size about 45-47% versus GQA.

GVA stores only grouped values and reconstructs content keys with a learned linear map absorbed into the query at decode time, while a small shared decoupled RoPE channel preserves positional information via a separately cached positional key. At 350M parameters trained on 30B FineWeb-Edu tokens, the 16-dimensional positional variant scores 44.18 average accuracy across five tasks versus 44.36 for GQA and 43.88 for MLA. Custom decoding kernels are in development with an open-source release planned.

Hugging Face daily papers · 9d agoAI research

Building a Production Greek-English Speech Recognizer

Engineering report details Sophea, a production Greek-English ASR reaching 4.26% WER on public English sets via ROVER ensemble and data-pipeline calibration.

Across 23 training iterations, two architectures, and nine production gates, no single data composition passed all gates; a three-model ROVER ensemble reached 9 of 9 gates and cut overlapping-speech WER from 53.35% to 37.87%. Calibrating an audio-quality filter against in-domain anchors reduced discarded scored Greek audio from 98.7% to 10.6%, and a pre-registered ablation traced a hallucination defect to one training-data package. The sophea/asr-k1 preview arbiter lists 4.26% average WER on eight public English test sets and 25.88% WER on live Greek noisy traffic; no weights or training data are released.

Hugging Face daily papers · 6d agoAI research

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 · 11d agoAI research

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.

The Rosetta system for the AlexandriaX-2026 shared task fine-tunes a LoRA adapter on NileChat-3B for context-aware English-to-dialectal Arabic dialogue translation. The adapter was additionally pretrained on MADAR and PADIC dialect corpora for the unconstrained track. It achieved spBLEU 26.10 (4th, constrained) and 25.09 (5th, unconstrained). External dialect pretraining improved only two of thirteen dialects while slightly degrading overall performance, indicating negative transfer.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face Blog · 29d agoAI tools & infra1

Real-SWE: Benchmarking AI models on private, real-world, enterprise codebases

Real-SWE benchmark tests coding agents on licensed private enterprise codebases; top model Fable 5.1 resolves only 38.8% of tasks.

Real-SWE is a new benchmark evaluating frontier AI coding agents on tasks drawn from private production codebases licensed from real companies, spanning billing, tax calculation, and cross-service migrations. Fable 5.1 with Claude Code leads at 38.8% resolution rate (pass@1 over eight runs), followed by GPT-6 Astra Codex CLI at 33.8% and Gemini 3.8 Flash Gemini CLI at 31.2%. Tasks use native harnesses and realistic tooling including Docker, Kubernetes, PostgreSQL, Redis, and Linear; median reference solutions edit 11 files versus 6 for DeepSWE and FrontierCode.

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.

OpenWAM: An Open, Modular Exploration Towards Systematic World-Action Model Pretraining

OpenWAM releases an open modular stack for world-action model pretraining, plus OpenWAM-alpha trained on about 6,400 hours of egocentric and robot data.

OpenWAM is an open research stack that factorizes World-Action Model pretraining into composable infrastructure, study, and model components with unified training, inference, and evaluation. Controlled experiments distill three principles on knowledge inheritance, world-action synergy, and out-of-domain generalization gains from embodied co-training. The resulting OpenWAM-alpha, pretrained on roughly 6,400 hours of egocentric human and robot data, achieves top-tier results across eight simulation benchmarks and real-robot tests spanning single-arm, bimanual, and dexterous embodiments. The full stack, including infrastructure, evaluation protocols, pretrained models, and data recipes, is released openly.

Hugging Face daily papers · 10d agoAI research

PARSER: Read in Parallel, Reason in Depth for Long-Context LLM Agents

PARSER uses parallel reader subagents and an RL-trained lead agent for long-context QA, beating baselines and cutting latency up to 11x.

The PARSER paper decouples reading from reasoning: frozen subagents each read one document chunk in parallel while an RL-optimized lead agent iteratively broadcasts queries and aggregates evidence in scatter-gather rounds. On multi-hop QA with 7K to 896K token contexts, a 4B-backbone PARSER beats the strongest sequential memory baseline by 5.7 points on average and 12.0 points at 896K tokens, and a 9B version surpasses DeepSeek-V4-Pro by 6.3 points. Controlled experiments show robustness to evidence position, order, and distance perturbations, with inference latency reduced by up to 11x.

Hugging Face daily papers · 11d agoAI research1

Atlas: Efficient Verifiable Semantic Search

Atlas delivers zero-knowledge proofs for HNSW semantic search, verifying RAG retrieval in under a second on SIFT1M and 2.0 seconds at 100M vectors.

Atlas lets a search provider prove that a query was answered correctly against a committed HNSW index without revealing the index, addressing provider deviations like truncation or bias. It combines offline preprocessing, a fixed-size-state restructuring of HNSW with a correctness proof, and timestep-tagged batching of per-step arguments. The system proves queries in under a second on SIFT1M and 2.0 seconds at 100 million vectors while preserving plaintext HNSW recall, and proven retrieval maintains end-to-end RAG answer quality at lower cost than prior verifiable retrieval systems.

arXiv cs.CR · 6d agoResearch1

Jackrong/Qwopus3.8-27B-Flash-GGUF — new model trending #26 on Hugging Face

Community fine-tune Qwopus3.8-27B-Flash, built on Qwen3.8-27B, cuts agent reasoning latency with 12.8% faster decoding and 80.7% MTP acceptance.

Jackrong released Qwopus3.8-27B-Flash, a fine-tune of Qwen3.8-27B optimized for long-running agent workloads, reporting 12.8% faster decoding and 80.7% multi-token-prediction acceptance. Training used roughly 1.5 million teacher-scored SFT examples filtered to the top 10%, followed by reinforcement training with NVIDIA NeMo-RL and GSPO. The author notes an explicit trade-off: MMLU-Pro mixed-set scores are lower than the base model, and a known bug can produce incorrect Python indentation. Author-provided benchmarks have not been independently verified.

Hugging Face trending models · 12d agoModel release1

Memory as Plans: World-Action Modeling with Memory-Grounded Planning

Researchers introduce MaP-WAM, decomposing memory-dependent robot manipulation into memory-grounded planning and plan-conditioned execution, achieving 83.3% on RMBench and 78% on real robots.

MaP-WAM converts long-term multimodal episodic memory — segment records with language instructions and sparse visual context — into compact plans of next-segment language goals and visual guidance. A World-Action-Progress model jointly predicts action chunks and execution progress, calibrating predictions via plan-observation alignment for adaptive segment transitions and closed-loop context updates. Structured attention keeps the executor context length fixed and enables key-value caching, yielding state-of-the-art 83.3% success on RMBench, 78.0% on real-robot tasks, and roughly constant inference latency as task history grows.

Hugging Face daily papers · 7d agoAI research

Characterizing Language Generation in the Limit: Finite Witnesses and a Separation-Width Hierarch

New work characterizes language generation in the limit via finite witnesses, proves a full separation-width hierarchy, and formalizes all results in Lean.

The paper fully characterizes when language generation in the limit is possible for arbitrary families over a countable universe: each target must admit a finite positive witness such that targets activated by any finite sample share an infinite common intersection. It defines positive separation width and proves every level of the resulting hierarchy occurs, with countable families admitting singleton witnesses and unions of families with infinite common cores requiring unbounded finite witnesses. The characterization, a universal normalization, and a diagonal capture lemma are machine-checked in the Lean proof assistant, with the development maintained on GitHub.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

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 · 6d agoAI research1

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 · 8d agoAI research

Transfer Learning for Evolving Domains

TrED formalizes transfer learning for domains whose data availability evolves over time, arguing classical settings are regimes along one trajectory, and remains unsolved.

The paper introduces Transfer Learning for Evolving Domains (TrED), formalizing transfer learning as a trajectory problem where target data and labels are progressively collected. TrED is specified by a data availability process fixed by the environment, a freely chosen learning protocol, and an evaluation criterion scoring the whole trajectory of models. Classical settings like domain generalization, domain adaptation, and multi-domain learning are recovered as regimes within this framework. The authors survey the literature and find most methods are tailored to a single regime, leaving TrED a well-posed open problem.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

“Network outage” disrupts Westfield Public Schools in New Jersey as ransomware group posts samples

A ransomware group posted stolen data samples after a districtwide network outage disrupted Westfield Public Schools in New Jersey.

Westfield Public Schools in New Jersey experienced a districtwide network outage during the first week of school, disrupting communications and digital instruction while classrooms stayed open. The district initially attributed the disruption to networking hardware failure across all schools and offices. A ransomware group has since posted data samples, indicating extortion activity tied to the incident.

DataBreaches.net · 7d agoRansomware

World in World: Explore the World with World Models

World in World is a training-free inference-time interface enabling camera-controlled rerendering, long-horizon revisiting, and motion transfer with frozen causal video world models.

The framework converts heterogeneous control evidence into camera- and time-labelled clean visual states that are read through the native self-attention of a frozen causal video model. Evidence includes source-video observations, target-view scene projections, geometry renderings for completing newly exposed regions, and retrieved generated states beyond the rolling cache. A correspondence router combines persistent point identities with geometry for token correspondences, while evidence-wise attention CFG independently regulates each auxiliary channel. The shared interface supports camera-controlled rerendering, long-horizon revisiting, and human-motion transfer without additional training.

Hugging Face daily papers · 7d agoAI research

Mathspace Data Breach Exposes Over 1 Million People

Mathspace breach exposed data of 1,079,819 Australian and New Zealand users via exploited Metabase zero-day CVE-2026-72898; ShinyHunters claimed responsibility.

Mathspace disclosed a breach affecting 1,079,819 students, teachers, staff, and parents in Australia and New Zealand. Attackers exploited the Metabase SQL injection zero-day CVE-2026-72898 (CVSS 10), patched August 6, and accessed Mathspace's self-hosted instance from August 10; ShinyHunters claimed the Metabase hacks. Exposed data includes names, usernames, emails, and login dates; no passwords, academic records, or credentials were taken.

SecurityWeek · 8d agoData breach in the wildCVE-2026-72898

Cognition's SWE-2 achieves 92.8 on Terminal-Bench 2.1

Cognition releases SWE-2, a 2.8T-parameter MoE coding model post-trained from Kimi K3, scoring 92.8 on Terminal-Bench 2.1.

SWE-2 is a proprietary mixture-of-experts model with 2.8T total parameters and 104B active per token, built on the Kimi K3 base with additional Cognition reinforcement-learning post-training for agentic coding. Vendor-reported benchmarks include FrontierCode 1.1 Main 50.0, DeepSWE 1.1 73.0, Terminal-Bench 2.1 92.8, and Terminal-Bench 4.0 27.3. It claims to be one point behind Claude Fable 5.1 on FrontierCode at a claimed 64% lower cost, but trails Fable 5.1 and GPT-6 Astra by a wide margin on long-horizon Terminal-Bench 4.0 tasks. The model is available today in Devin Desktop and CLI, with no published weights, no per-token API pricing, and all figures pending independent replication.

Hacker News · AIupdated · 4d agofirst · 6d agoModel release 10 sourcesHN 40↑ · 18 comments

Real-World Knowledge-Guided Change Data Synthesis for Remote Sensing

Researchers introduce KnowChange, a framework that uses pretrained vision-language models to synthesize realistic change-detection training data for remote sensing.

KnowChange is a knowledge-guided change data synthesis framework that leverages pretrained vision-language models to reason about plausible change locations and class transitions from pre-change scenes and desired change types. It addresses the limited class-transition coverage and inflexibility of handcrafted rule-based synthesis methods, enabling diverse change types in a unified pipeline. Experiments show KnowChange-generated data outperforms existing synthetic datasets in both synthetic-to-real transfer and synthetic data augmentation, despite compact generation scale.

Hugging Face daily papers · 23d agoAI research

MobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control

MobileVLA-R1 2.0 couples chain-of-thought reasoning with RL for mobile robot control, gaining 10 points on real Unitree G1 tasks.

MobileVLA-R1 2.0 is an RL-enhanced vision-language-action framework that explicitly couples structured embodied reasoning with executable mobile robot control via supervised Chain-of-Thought alignment and reinforcement learning. A reasoning-conditioned action decoder maps multimodal reasoning representations to task-level action targets, decoupling high-level action generation from robot-specific actuation for both locomotion and manipulation. It achieves an average 1.6 point SR improvement on VLN-CE and a 10.0 point improvement in full-task success on real-world Unitree G1 mobile manipulation, with evaluations covering navigation, quadruped control, and real deployments on Unitree Go2 and G1 robots.

Hugging Face daily papers · 12d agoAI research