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Salesforce and Nvidia’s new reasoning model is everything the AI labs should fear

Salesforce and Nvidia launch Koa, Salesforce's first reasoning model, built on Nvidia's open-weight Nemotron and post-trained on synthetic sales and support data.

Salesforce announced Koa at Dreamforce, its first reasoning model, built on Nvidia's open-weight Nemotron and post-trained with synthetic data mimicking sales and customer-support scenarios rather than real customer data. Koa will be offered through the Agentforce platform's AI gateway as a cheaper, token-efficient alternative to closed frontier models like Claude and ChatGPT for enterprise tasks. Salesforce simultaneously announced a ClaudeForce partnership with Anthropic keeping customer data inside Salesforce's infrastructure.

TechCrunch · AISep 15, 12:00 UTC · 1d agoModel release1

‘Now We Can Know Everything and Do Anything,’ Jensen Huang Says at Dreamforce

Salesforce unveiled Koa, its first CRM reasoning model post-trained on NVIDIA Nemotron 3 Super, announced during Jensen Huang's Dreamforce keynote.

At Salesforce Dreamforce, NVIDIA CEO Jensen Huang joined Marc Benioff onstage as Salesforce announced Koa, its first CRM reasoning model, post-trained from NVIDIA Nemotron 3 Super using NeMo RL, NeMo Gym, and NeMo AutoModel. Koa was fine-tuned on a proprietary synthetic dataset drawn from nearly three decades of enterprise CRM deployments across 14+ industries, with no customer data used in training or inference. On Salesforce's CRM Bench of real-world tasks, Koa matches or exceeds leading model performance on CRM actions with 3x fewer errors. Koa already powers an employee agent in Slack, enters customer pilots in October with Formula 1, UChicago Medicine, Baxter Credit Union, 1-800Accountant, Engine, and Xero, and reaches general availability in Winter 2026 in U.S. regions.

NVIDIA BlogSep 15, 22:24 UTC · 19h agoAI industry

Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models

Researchers introduce KoNA, a benchmark exposing vision-language models' failures at selective non-compliance, plus fine-tuning that improves refusal and abstention accuracy.

KoNA is a benchmark for evaluating selective non-compliance in vision-language models across five categories: False Premise, Visual Inaccessibility, Universal Unknown, Task Feasibility and Safety. It tests both query-level and component-level non-compliance using paired single and compound queries, and evaluations across diverse VLMs show models often fail to refuse, correct or abstain appropriately, with failures worsening on compound queries. Fine-tuning VLMs on KoNA examples substantially improves non-compliance accuracy while largely maintaining performance on fully answerable tasks.

Hugging Face daily papersSep 3, 20:00 UTC · 12d agoAI research1

Multi-Step Tool-Calling over Korean Open Public APIs: A Benchmark and a Data-Synthesis Recipe

Researchers introduce KOPA-Bench, a 145-task Korean public API tool-calling benchmark, and EDGE, an execution-grounded data synthesis method.

An arXiv paper presents KOPA-Bench, a benchmark of 145 real-world tasks chaining multiple tool-calls across live Korean government APIs, motivated by data-sovereignty requirements for on-premise open-source LLM agents. It also introduces EDGE, an execution-grounded dynamic graph that keeps only tool-output-to-input links verified by live API calls before synthesizing executable multi-step trajectories. A 9B model fine-tuned with GRPO on the resulting dataset nearly matches its untuned 27B family sibling on KOPA-Bench and improves on the BFCL benchmark.

arXiv cs.AI / cs.LG / cs.CLSep 4, 17:44 UTC · 12d agoAI research1

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

RoboSPA introduces a 527K-trajectory benchmark with 280 task variants showing current VLA models struggle with spatial reasoning and long-horizon planning.

RoboSPA is a large-scale robotic manipulation dataset and benchmark for diagnosing embodied reasoning in vision-language-action models, covering fine-grained spatial reasoning and long-horizon procedural planning. It spans 10 task categories and 56 base tasks instantiated across five difficulty levels for 280 variants, with 527K trajectories collected across multiple embodiments and diverse scenes. Diagnostic metrics go beyond binary success rates, and experiments show current VLA models struggle with complex spatial relations, precise low-level execution, and memory-intensive planning.

Hugging Face daily papersSep 3, 20:00 UTC · 12d agoAI research

Augustinian BabyLM: What Ostensive Definition Can and Cannot Teach a Small Language Model

Study shows visually grounded token embeddings in a small masked LM persist through training and improve object-property knowledge, but escape standard BabyLM benchmarks.

The paper implements ostensive definition for a small DeBERTa masked language model trained on 10M words, seeding visually grounded tokens with embeddings derived from labeled image regions before training. Visual initialization leaves a persistent, seed-replicated advantage on object-property knowledge (COMPS) and a corpus-tailored Visual-Property Swap benchmark covering color, material, size, and shape, but has no effect on most BabyLM grammar benchmarks. Synthetic grounding of previously unseeded words causally transfers the advantage to exactly those words.

arXiv cs.AI / cs.LG / cs.CLSep 10, 17:43 UTC · 6d agoAI research

IFM/K2-Horizon-MoVA-36B-A4B — new model trending #15 on Hugging Face

IFM released K2-Horizon-MoVA-36B-A4B, an open-weights 36B-parameter MoE model with 4B active parameters and native 512K context.

IFM released the final checkpoint of K2-Horizon-MoVA-36B-A4B, a sparse Mixture-of-Experts model using Mixture-of-Values (MoVA) attention with 36B total and 4B active parameters. The model supports native 524,288-token context and reportedly outscores open-weight dense and MoE models up to 15x its size on agentic and reasoning benchmarks, while competing against closed frontier models. Intermediate checkpoints, training data, the training recipe, and training code are slated for public release.

Hugging Face trending modelsSep 1, 23:01 UTC · 14d agoModel release

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.CLSep 9, 16:15 UTC · 7d agoAI research1

KlueセキュリティインシデントとRecorded Futureへの影響

Recorded Future disclosed a Klue incident that exposed some Salesforce business data, including contacts and emails, via a compromised OAuth token.

Recorded Future disclosed that unauthorized activity in marketing vendor Klue's integration layer, starting June 12, 2026 and contained the same day, affected some of its Salesforce data through a compromised OAuth token in the Salesforce-Klue integration. Impacted fields are limited to business data such as customer contact names, email addresses, and possibly business contract information. No evidence indicates Recorded Future's core platform, Intelligence Graph, internal databases, or customer platform data were accessed. The company revoked all relevant OAuth tokens, coordinated with Salesforce and law enforcement, and began reviewing all third-party Salesforce integrations.

Recorded FutureAug 12, 00:00 UTC · Aug 12, 2026Data breach

CUA-Universe: A Scalable and Dynamic Environment for Hybrid GUI+CLI Agents

Researchers introduce CUA-Universe, a pipeline turning real desktop software into hybrid GUI+CLI agent environments, lifting a 9B model's OSWorld success rate.

CUA-Universe is an environment-to-data pipeline that converts real desktop applications into hybrid GUI+CLI environments, scaling to 16 applications via App-Forge, Task-Weave, and Path-Steer. Training on its harvested trajectories shifted a 9B model toward effective GUI+CLI orchestration, yielding +39.3 points on CUA-Verse, +16.8 points success rate on OSWorld, and +7.84 points on OSWorld-MCP while cutting steps and tokens by up to 57% and 60%. The work addresses the scarcity of scalable hybrid environments for computer-use agents.

arXiv cs.AI / cs.LG / cs.CLSep 4, 17:26 UTC · 12d agoAI research1

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

RoboSPA introduces a 527K-trajectory robotic benchmark with 280 task variants exposing VLA model weaknesses in spatial reasoning and long-horizon planning.

RoboSPA is a large-scale robotic manipulation dataset and benchmark for diagnosing embodied reasoning in vision-language-action models, spanning fine-grained spatial reasoning and long-horizon procedural planning. It covers 10 task categories and 56 base tasks instantiated across five difficulty levels for 280 variants, with 527K trajectories collected across multiple embodiments. Experiments on representative VLA models show current systems struggle with complex spatial relations, precise low-level execution, and memory-intensive planning.

arXiv cs.AI / cs.LG / cs.CLSep 4, 16:19 UTC · 12d agoAI research

CISA Adds Six Exploited Flaws to KEV, Including NetScaler, Linux, and SQL Server Bugs

CISA added six actively exploited flaws to KEV, led by Citrix NetScaler CVE-2026-8452, with federal patch deadlines set.

CISA added six flaws to the KEV catalog on August 27, 2026, citing evidence of active exploitation, led by CVE-2026-8452, an improper buffer restriction in Citrix NetScaler ADC and Gateway that can cause denial-of-service. Defused Cyber and Previdian reported active exploitation of CVE-2026-8452, with 36 attempts over 12 days from 12 attacker IPs deploying web shells x.php and z.php. The other additions cover SQL Server RCE (CVE-2019-1068), Linux kernel out-of-bounds write (CVE-2022-0995), Red Hat ABRT and libuser privilege escalations (CVE-2015-5287, CVE-2015-3246), and AjaxPro deserialization RCE (CVE-2021-23758). FCEB agencies must patch CVE-2019-1068 and CVE-2026-8452 by August 29, 2026, and the rest by September 9, 2026.

The Hacker NewsAug 27, 07:05 UTC · 20d agoExploit / PoC in the wildCVE-2019-1068 CVE-2026-8452 CVE-2022-0995+3 CVEs

Think Before You Link: Rarity, Reasoning, and Retrieval in Multilingual Entity Linking

Training-free reasoning-plus-retrieval framework lifts multilingual multimodal entity linking accuracy by 6.9% overall and up to 23.3% on rare entities.

The paper broadens rarity measurement in multimodal entity linking using knowledge-graph structural metrics beyond popularity-based pageview metrics, identifying many rare entities that popularity metrics miss. Across these rare-entity slices, state-of-the-art accuracy drops by 15.4-39.9%, exposing distinct failure modes under different rarity definitions. The proposed training-free framework iteratively searches and reasons over Wikipedia with a reasoning-capable vision-language model; experiments show reasoning and retrieval are complementary. On the MERLIN benchmark covering Hindi, Indonesian, Japanese, Tamil, and Vietnamese, the system improves overall accuracy by 6.9% and up to 23.3% on rare entities, with MERLIN-Rare test slices released.

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

Former OpenAI researcher builds an AI model that judges options instead of writing text

TypeSafe AI launches Jev, a judgment-only model built by ex-OpenAI staff that classifies inputs with 70-500 ms latency instead of generating text.

Startup TypeSafe AI, co-founded by former OpenAI researcher and InstructGPT co-author Diogo Almeida, introduced Jev, a model that scores developer-defined answer options with probabilities rather than generating free-form text. The company claims 70-500 ms responses, parallel multi-question evaluation, and $0.042 per million input tokens with free outputs, targeting request routing, sales intent scoring, and assistant guardrail checks. Benchmarks are self-built and not independently verified, the 'no hallucination' guarantee only covers output structure, and access is currently via waitlist.

The Decoder15:19 UTC · 2h agoAI industry

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.CLSep 14, 16:49 UTC · 2d agoAI safety & security

Identifying a BOLA Vulnerability in Harbor, a Cloud

Unit 42 found a BOLA flaw, CVE-2024-22278 (CVSS 6.4), letting Maintainers improperly alter Harbor project metadata; fixed in versions 2.9.5, 2.10.3, and 2.11.0.

Unit 42 researchers identified a broken object-level authorization flaw, CVE-2024-22278, in Harbor, a CNCF-graduated cloud-native container registry with 1.8 million downloads. The flaw (CVSS 6.4) lets users with the Maintainer role create, update, and delete project metadata, actions reserved for ProjectAdmin, risking data exposure, integrity compromise, and circumvention of vulnerability scanning. Harbor patched the issue in versions 2.9.5, 2.10.3, and 2.11.0. The finding came from Unit 42's automated BOLA detection tool built on generative AI.

Palo Alto Unit 42Aug 17, 12:35 UTC · Aug 17, 2026Vulnerability CVE-2024-22278

CISA Adds One Known Exploited Vulnerability to Catalog

CISA added CVE-2026-76461, an actively exploited SQL injection in Cisco Secure Email Gateway, to the KEV catalog.

CISA added CVE-2026-76461, a SQL injection vulnerability in Cisco Secure Email Gateway, to its Known Exploited Vulnerabilities (KEV) Catalog based on evidence of active exploitation. BOD 26-04 requires Federal Civilian Executive Branch agencies to prioritize rapid remediation of KEV vulnerabilities on publicly exposed assets and to check whether systems were compromised before patching. CISA encourages all organizations to adopt risk-based vulnerability management and prioritize KEV remediation.

CISA Advisoriesupdated 13:57 UTC · 4h agofirst Sep 14, 12:00 UTC · 2d agoExploit / PoC in the wild 17 sources CVE-2026-76461

Technical Manual for a Toolkit for Measuring Contextual Individuation in Transformer Language Models

An open methodology toolkit measures whether transformer language models contextualize fixed word forms across domains using bridge forms and layer-wise silhouette analysis.

The manual documents an open toolkit built around 'bridge forms' - identical written words recurring across two or more subject domains with a different sense in each - to test whether transformer language models individuate word occurrences by context beyond the embedding layer. It covers declarative specification of bridge forms, Wikipedia corpus acquisition, occurrence localization, layer-wise representation extraction, domain-pairwise silhouette measurement, and visualization, justifying each choice against failure modes such as sense contamination and subword-tokenization misalignment. It is a methodological and implementation reference and reports no empirical results.

arXiv cs.AI / cs.LG / cs.CLSep 4, 16:38 UTC · 12d agoAI research

Harnessing LLMs for Automating BOLA Detection

Unit 42's BOLABuster methodology uses LLMs to automate detection of broken object-level authorization vulnerabilities, uncovering flaws in Grafana, Harbor, and Easy!Appointments.

Palo Alto Unit 42 details BOLABuster, a methodology combining large language models with heuristics to automate detection of broken object-level authorization (BOLA) flaws, which traditional fuzzing and static analysis struggle to find. The approach uses LLM reasoning to understand application logic, map endpoint dependency relationships, and generate and interpret test cases. It found CVE-2024-1313 in Grafana, CVE-2024-22278 in Harbor, and 15 CVEs in Easy!Appointments. The team is continuing to hunt for BOLAs in open-source and internal projects.

Palo Alto Unit 42Aug 17, 12:34 UTC · Aug 17, 2026Research CVE-2024-1313 CVE-2024-22278 CVE-2023-3285+14 CVEs

U.S. CISA adds ownCloud, Linux Kernel, and JFrog Artifactory flaws to its Known Exploited Vulnerabilities catalog

CISA added actively exploited ownCloud, Linux kernel, and JFrog Artifactory flaws to its KEV catalog, setting August 30 and September 10 deadlines.

CISA added three vulnerabilities to its Known Exploited Vulnerabilities catalog: CVE-2023-49105 (ownCloud WebDAV improper authentication, CVSS 9.8), CVE-2026-53362 (Linux kernel IPv6 out-of-bounds write, CVSS 7.8), and CVE-2026-66384 (JFrog Artifactory path traversal, CVSS 5.3). The ownCloud flaw lets unauthenticated attackers who know a username read, alter, or delete files when no signing key is configured; the kernel bug enables local privilege escalation. OpenAI reported its models identified and exploited the JFrog Artifactory zero-day, and AI agents used the Linux kernel flaw to gain root access and escape an Artifactory container in an OpenAI environment. Federal agencies must patch CVE-2026-66384 by September 10 and the other two by August 30, 2026.

Security AffairsAug 28, 13:56 UTC · 19d agoExploit / PoC in the wildCVE-2023-49105 CVE-2026-53362 CVE-2026-663841

UC Berkeley Researchers Release CUA-Lite, an Open Platform Unifying Sandboxes, Data, Evaluation and RL for Computer-Use Agents

UC Berkeley's CUA-Lite is an open platform unifying computer-use agent sandboxes, datasets, evaluation and RL; Lite.OSWorld cuts OSWorld memory 4.1 GB to 0.9 GB.

UC Berkeley researchers released CUA-Lite, an open platform placing agents, environments, traces, and training for computer-use agents behind one action space, one LiteSample schema, and one command across desktop, browser, and mobile. Lite.OSWorld reproduces the OSWorld task suite and evaluators in plain Docker containers (0.9 GB RAM vs 4.1 GB, cold start 23.8s, ~4.6× more parallel instances), with scores matching the QEMU/KVM VM across 13 models. The platform claims 30k+ verifiable tasks, 15+ benchmarks, 10+ agents, and 20+ datasets on Hugging Face including Aguvis, OpenCUA, and ScaleCUA. A documented SFT run lifts Qwen3-VL-2B-Instruct mean episode return from 0.138 to 0.237 on the 332-task lite.osworld split.

MarkTechPostSep 6, 06:11 UTC · 10d agoAI tools & infra1

CISA Adds Three Known Exploited Vulnerabilities to Catalog

CISA added three actively exploited vulnerabilities — two JFrog Artifactory and one ConnectWise ScreenConnect — to its KEV Catalog.

CISA added CVE-2026-42016 (JFrog Artifactory incorrect authorization), CVE-2026-42018 (JFrog Artifactory improper authentication), and CVE-2026-84869 (ConnectWise ScreenConnect improper privilege management and missing authorization) to the Known Exploited Vulnerabilities Catalog based on evidence of active exploitation. BOD 26-04 requires Federal Civilian Executive Branch agencies to prioritize rapid remediation of such high-risk vulnerabilities on publicly exposed assets and to check for prior compromise. CISA urges all organizations to adopt risk-based vulnerability management and prioritize KEV remediation.

CISA AdvisoriesSep 11, 12:00 UTC · 5d agoExploit / PoC in the wildCVE-2026-42016 CVE-2026-42018 CVE-2026-84869

CISA Adds Seven Known Exploited Vulnerabilities to Catalog

CISA added seven actively exploited vulnerabilities to its KEV catalog, including SonicWall SMA1000 SSRF and command injection flaws.

CISA added seven vulnerabilities with evidence of active exploitation to its Known Exploited Vulnerabilities catalog on September 2, 2026. The additions cover Sangoma Switchvox SQL injection (CVE-2026-9586), Kludex Starlette request smuggling (CVE-2026-48710), Kestra OS command injection (CVE-2026-49869), BerriAI LiteLLM (CVE-2026-59822) and JFrog Artifactory (CVE-2026-82329) authentication flaws, and SonicWall SMA1000 SSRF (CVE-2026-83548) and command injection (CVE-2026-83549) vulnerabilities. Under BOD 26-04, federal civilian agencies must prioritize rapid remediation of KEV-listed vulnerabilities on publicly exposed assets.

CISA AdvisoriesSep 2, 12:00 UTC · 14d agoExploit / PoC in the wildCVE-2026-9586 CVE-2026-48710 CVE-2026-49869+4 CVEs

Jalapeño’s first results show industry-leading speed and efficiency in AI inference

OpenAI's Jalapeño custom inference chip shows faster, more power-efficient inference with higher throughput and lower latency.

OpenAI announced first results for Jalapeño, its custom AI inference chip. The company claims industry-leading speed and efficiency, delivering higher throughput and lower latency for modern models compared with existing options. The chip targets more power-efficient serving of large models at scale.

OpenAI NewsAug 25, 07:00 UTC · 22d agoAI industry

CISA review makes the case for eliminating vulnerability classes

CISA's FY2024-2025 vulnerability review urges eliminating recurring vulnerability classes, finding 41.5% of 2025 KEV entries map to persistent 'stubborn weaknesses'.

CISA's Vulnerability Review for fiscal years 2024 and 2025 found most compromises stemmed from opportunistic exploitation of known, exposed vulnerabilities rather than nation-state zero-days or advanced tradecraft. The review found 41.5% of 2025 KEV catalog entries map to 'stubborn weaknesses' - injection flaws, improper input validation, memory-safety failures, path traversal and broken access control - recurring on the CWE Top 25 since 2019. CISA advocates Secure by Design practices, vulnerability class elimination, and buyer-driven 'Secure by Demand' contract requirements, while warning that AI-enabled vulnerability discovery will soon accelerate exploitation.

Help Net SecuritySep 1, 00:00 UTC · 15d agoPolicy & legal

NCP-ArchPreview Technical Report: Moving towards Latent Space Language Models through Next Concept Prediction

An 8.9B-parameter latent-space language model using next-concept prediction matches OLMo-3-7B pretraining loss with only 51.3% of the training tokens.

NCP-ArchPreview augments next-token prediction with Next Concept Prediction over a product-quantized concept vocabulary built from hidden states, trained jointly end-to-end. The 8.9B model was trained on 5.73T tokens from the Dolma-3 dataset, the largest latent-space language model demonstration to date. It consumes 51.3% of the tokens to reach OLMo-3-7B's final pretraining loss and outperforms it by 2.45 points on the downstream macro-average, including a 5.99-point GSM8K gain. The learned latent space also enables lightweight domain adaptation via a 17M-parameter VQ module and improves speculative drafting accepted length by 4.17%.

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

ACEA: An Adversarial Co-Evolution Arena for Head-to-Head Red-Team and Blue-Team LLM Testing

ACEA is a pluggable arena scoring LLM red-team attackers and blue-team defenses head-to-head with an LLM judge and verifiable leakage ground truth.

ACEA connects pluggable red- and blue-team adapters to a shared target LLM through the model-agnostic ASAP HTTP protocol and scores attack and defense rates per adversarial round. Canonical seeded secrets provide verifiable ground truth that separates real leakage from hallucination, and attacks are delivered to the target even when blocked to measure raw potency. The platform adds real-time battle visualization, failure-localizing end-of-battle reports, and an optional in-context improvement loop that feeds advisory hints between rounds.

arXiv cs.CRSep 8, 04:57 UTC · 8d agoAI safety & security1

CISA Adds One Known Exploited Vulnerability to Catalog

CISA added CVE-2026-85706, an actively exploited GitLab path traversal flaw, to its KEV Catalog, requiring federal agencies to prioritize patching.

CISA added one vulnerability to its Known Exploited Vulnerabilities Catalog based on evidence of active exploitation: CVE-2026-85706, a path traversal vulnerability in GitLab Community Edition and Enterprise Edition. Under Binding Operational Directive (BOD) 26-04, Federal Civilian Executive Branch agencies must prioritize rapid remediation of KEV-listed vulnerabilities on publicly exposed assets, including checking whether systems were compromised before the patch was applied. While BOD 26-04 binds only FCEB agencies, CISA encourages all organizations to adopt risk-based vulnerability management and prioritize KEV remediations.

CISA Advisoriesupdated Sep 15, 00:52 UTC · 1d agofirst Sep 11, 12:00 UTC · 5d agoExploit / PoC in the wild 18 sources CVE-2026-85706

Dynin-Robotics: Omnimodal Unified Diffusion Vision-Language-Action Model

Dynin-Robotics unifies action, goal, and dynamics prediction in one omnimodal masked-diffusion VLA model, reaching 78.4% success on Franka Research 3 manipulation tasks.

Built on the Dynin-Omni masked-diffusion backbone, the model represents language, observations, goals, and actions as discrete tokens and is continually pretrained on roughly 1.33 million trajectories from 48 Open X-Embodiment datasets. The shared trajectory interface enables test-time scaling via goal prediction, action-candidate evaluation, and joint action/future-state refinement. It achieves competitive results on LIBERO and zero-shot LIBERO-Plus, 78.4% average success across four Franka Research 3 conditions, and up to 29.2x faster model-side action decoding from a block-parallel implementation.

Hugging Face daily papersupdated Sep 11, 16:49 UTC · 5d agofirst Sep 10, 20:00 UTC · 5d agoAI research 2 sources

Right Tool, Right Job: Native-Language Evaluation, Tokenizer Sensitivity, and Methodological Findings from a French-Only BabyLM

French BabyLM entry METRON-FR (125M GPT-2, 92.47M words) shows tokenizer artifacts dominate child-scale zero-shot evaluation; proposes standard diagnostics.

METRON-FR is a 125M-parameter GPT-2 pretrained on 92.47M French words, submitted to the BabyLM 2026 Strict track, scoring 85.97% on the native Quebec-French QFrBLiMP benchmark and 62.80% on the BabyLM-weighted leaderboard. A cross-lingual GLUE protocol combining French task-data translation with rank-16 LoRA shows relational tasks gain while world-knowledge tasks regress. Bilingual Lexicon Induction reaches p@1 of 68.84%, 18x above chance, and ablations show single-token zero-shot scoring is dominated by tokenizer and template artifacts at child scale.

arXiv cs.AI / cs.LG / cs.CLSep 15, 16:43 UTC · 1d agoAI research