Search: “model-releases”

Inferred Generative-Process Diversity Predicts Correlated Failure Across Language Models

arXiv:2609.03422v1 Announce Type: new Abstract: Diversity is a widely observed factor in the resilient function of collective systems, yet the type of diversity that matters depends on the properties

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Interface-Induced Trajectory Censoring

DGX agent

arXiv:2609.03966v1 Announce Type: new Abstract: Agent evaluations report a tool-call rate read off the serving stack. That number can be zero while the model is emitting well-formed calls: the interfa

model-releasesarxiv-cs-ai

4 Sept 2026

Introducing SINFONIA: Symplectic, slimplectic and Magnusian (Neural) Flows for Orbital Numerical Integration and Acceleration

arXiv:2609.03329v1 Announce Type: cross Abstract: Long-duration gravitational-wave modelling must resolve fast orbital motion together with slow dissipative evolution while preventing small numerical

Investigating the Ability of Large Language Models to Analyze Recipes for Diabetes

arXiv:2609.03967v1 Announce Type: cross Abstract: Several studies have evaluated the ability of Large Language Models (LLMs) for meal planning, yielding positive outcomes. These models can process nat

IRWOZ 2.0: A Large Language Model-driven Dialogue Dataset for Industrial Robot Conversations

arXiv:2609.04030v1 Announce Type: new Abstract: IRWOZ has improved industrial human-robot interaction (HRI) dialogue systems through domain-specific annotations. However, its initial version contains

It happened again... this time OpenAI's rogue agents cyber-attacked (well, spammed) a dormant German wiki and used it to share the answers t…

model-releasessimon-willison--x

It happened again... this time OpenAI's rogue agents cyber-attacked (well, spammed) a dormant German wiki and used it to share the answers to a benchmark they were training against https://simonwillis

It is funny that the Fermat's Last Theorem proof description, short as it is, still smells so much of Claude ('names each step and the Lean …

model-releasesethan-mollick--x

It is funny that the Fermat's Last Theorem proof description, short as it is, still smells so much of Claude ('names each step and the Lean Theorem that carries it'). Anthropic just uploaded a Lean 4

It's the Problem, Not the Path: Budget and Difficulty Confounds in LLM Reasoning Trajectories

arXiv:2609.03436v1 Announce Type: cross Abstract: Reasoning traces of large language models are widely read as containing 'breakthrough' moments and early-legible fates. Both readings rest on measurem

Jina-OCR-v1: Efficient Document Parsing with Speculative Decoding and Dense Verifiable Rewards

arXiv:2609.03181v1 Announce Type: new Abstract: We present Jina-OCR-v1, an end-to-end document parsing model built to serve on low-budget GPUs. It combines the compressed-vision encoder and the 3B mix

KC-Bench: A Dynamic Interactive Benchmark for Evaluating Knowledge Conflicts in LLM Agents

arXiv:2609.03588v1 Announce Type: new Abstract: As LLMs increasingly act through tools, they must reconcile user instructions, parametric knowledge, and dynamic environmental observations before takin

KernelFoundry: Hardware-aware evolutionary GPU kernel optimization

arXiv:2603.12440v2 Announce Type: replace-cross Abstract: GPU kernel optimization challenges LLMs beyond standard coding tasks, as it requires an understanding of hardware architecture, parallel compu

KhatianDoc: A Human-Verified Benchmark Diagnosing Multimodal LLM Failure on Bengali Legal Land Records

arXiv:2609.03597v1 Announce Type: new Abstract: Land ownership in Bangladesh is recorded in Ana-Ganda-Kora-Kranti-Til, a base-16 positional fraction system with dedicated Unicode glyphs, no mainstream

Last Translation Benchmark

arXiv:2609.04173v1 Announce Type: new Abstract: For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases.

Latent Energy Action Planning with World Models

arXiv:2609.03294v1 Announce Type: new Abstract: Latent world models support efficient model predictive control from high-dimensional observations, yet optimizing a single learned latent objective can

Learning Constraints-Based Adaptive Hypergraph Neural Networks for Solving Vehicle Routing Problems

arXiv:2503.10421v2 Announce Type: replace Abstract: The application of learning based methods to vehicle routing problems has emerged as a pivotal area of research in combinatorial optimization. These

Learning What Not to Forget: Long-Horizon Agent Memory from a Few Kilobytes of Learning

arXiv:2606.20954v2 Announce Type: replace-cross Abstract: Long-running language-model systems accumulate interaction history that outgrows the context window, so they must continually evict. When an e

LevelSyn: Physical-Aware Logic Synthesis via Level-Asynchronous Graph Neural Networks

arXiv:2609.03594v1 Announce Type: cross Abstract: As integrated circuit technology scales into the nanometer regime, the traditional disconnect between logic synthesis and physical design has led to s

LexIssue: Benchmarking Legal Issue Identification in Chinese Civil Litigation

arXiv:2609.02954v1 Announce Type: new Abstract: Identifying the issues disputed between litigating parties is a crucial component of real-world litigation. However, legal issues remain comparatively u

LightEMMA: A Longitudinal Evaluation of Vision-Language Models for Autonomous Driving

arXiv:2505.00284v3 Announce Type: replace-cross Abstract: Rapid advances in vision-language models (VLMs) have generated growing interest in their application to autonomous driving. A prevailing assum

LLaDA-Image: Building Strong Image Generators with Fully Open Training Recipes

arXiv:2609.03796v1 Announce Type: cross Abstract: We introduce LLaDA-Image, a unified framework that pairs a 6B Diffusion Transformer (DiT) trained from scratch with a frozen vision-language understan

LLM-Guided Reinforcement Learning for Adaptive NPC Behavior in Multi-Agent Combat Games

arXiv:2609.02931v1 Announce Type: cross Abstract: Scripted and rule-based non-player characters (NPCs) in combat video games often exhibit predictable behaviors that experienced players can exploit, w

LLMZero: Discovering Adaptive Training Strategies for RL Post-Training via LLM Agents

arXiv:2606.18388v2 Announce Type: replace-cross Abstract: RL post-training strategies are dataset-dependent and reveal a recurring empirical pattern: capacity parameters accumulate monotonically acros

Lngram v2: Latent N-Gram Memory with Interpretable Discrete Representations

arXiv:2609.03426v1 Announce Type: new Abstract: Transformers lack a native lookup mechanism, requiring repeated dense computation to recognize and reuse local static patterns. Lngram v1 introduces tok

Long-Horizon Consistent and Interaction-Aware World Models for Multi-Style End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2609.03225v1 Announce Type: new Abstract: End-to-end autonomous driving has increasingly adopted world model-based reinforcement learning frameworks to improve learning efficiency through extit{

LongCounsel-8: A Benchmark Suite for Longitudinal Depression Tracking from Multi-Session Counseling Dialogues

arXiv:2609.03507v1 Announce Type: cross Abstract: Tracking depression from multi-session counseling dialogues requires estimating both current symptom severity and how it changes across sessions. Yet

Lost in Reordering: Structural Sensitivity of Multilingual LLMs under Semantics-Preserving Perturbations

arXiv:2609.03511v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate strong multilingual reasoning performance, yet their robustness to semantics-preserving structural variation re

LRConv-NeRV: Low Rank Convolution for Efficient Neural Video Compression

arXiv:2603.18261v2 Announce Type: replace-cross Abstract: Neural Representations for Videos (NeRV) encode entire video sequences within neural network parameters, offering an alternative paradigm to c

Making Every Tool Call Count: Necessary Tool-Evidence Path Rewards for Agentic Vision-Language Models

arXiv:2609.03493v1 Announce Type: new Abstract: Modern vision-language models (VLMs) can directly answer many image-grounded questions, yet they often struggle with complex queries requiring fine-grai

Margins, Not Windows: Training-Free Per-Step Lossy Speculative Decoding

arXiv:2609.02897v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting candidate tokens and verifying them in parallel. Tree-attention drafters such as EAGLE-3 are

Measuring Harmfulness of Computer-Using Agents

arXiv:2508.00935v3 Announce Type: replace-cross Abstract: Computer-using agents (CUAs), which can autonomously control computers to perform multi-step actions, might pose significant safety risks if m

MedQA-MM: Shortcuts Behind Medical Visual Reasoning

arXiv:2609.03261v1 Announce Type: cross Abstract: A benchmark score credits final answers, but not the route by which an item can be answered. In medical multimodal multiple-choice questions (MCQs), t

MetaStructAtlas: A Grounded 3D Vision-Language Dataset and Benchmark for Functional and Structural Reasoning in Whole-Body PET/CT

model-releasesarxiv-cs-cv

arXiv:2609.03690v1 Announce Type: new Abstract: The joint interpretation of metabolic function and anatomical structure is essential for clinical diagnosis in whole-body PET/CT. Although recent advanc

Mind the Gap: Robustness Risks in PII Detection Systems

arXiv:2609.03464v1 Announce Type: new Abstract: Personally Identifiable Information (PII) detection is a foundational component of data protection infrastructure where missed entities constitute direc

MINERVA: How Small Can a Manipulation Policy Be and Still Solve LIBERO?

model-releasesarxiv-cs-ro

arXiv:2609.03715v1 Announce Type: new Abstract: Vision-language-action (VLA) models with billions of parameters now dominate the LIBERO manipulation benchmark, but the model capacity actually required

Mistral is bringing @aiDotEngineer back to Paris. After last year’s sold-out edition, our VP of Engineering Lélio Renard-Lavaud joins speake…

model-releasesmistral-ai--x

Mistral is bringing @aiDotEngineer back to Paris. After last year’s sold-out edition, our VP of Engineering Lélio Renard-Lavaud joins speakers from @bfl_ai , @cognition, @huggingface, and more. Explor

MSign: An Optimizer Preventing Training Instability in Large Language Models via Stable Rank Restoration

arXiv:2602.01734v2 Announce Type: replace Abstract: Training instability remains a critical challenge in large language model (LLM) pretraining, often manifesting as sudden gradient explosions that wa

New from the LangSmith Signal. Over the last 2 weeks, we looked at which models teams reach for, and which ones are doing the work. ✅ Reach:…

model-releasesharrison-chase--x

New from the LangSmith Signal. Over the last 2 weeks, we looked at which models teams reach for, and which ones are doing the work. ✅ Reach: gpt-4o-mini was used by 13% of orgs ✅ Work: gpt-4.1-mini sa

Not All LLM Workloads Are Equal: Benchmarking TPU Performance on Classification vs. Generation

model-releasesgoogle-cloud-ai

Moving Large Language Models (LLMs) from experimental prototypes into enterprise production exposes a critical truth: your infrastructure dictates both your performance ceilings and your unit economic

ObserverBench: Testing Mechanistic Estimates for Intervention and Control

arXiv:2609.03026v1 Announce Type: cross Abstract: Mechanistic interpretability is increasingly used to guide interventions such as activation steering, circuit removal, and safety monitoring. Yet an i

Occupancy-based Quantile Risk Control

arXiv:2609.03104v1 Announce Type: cross Abstract: Conformal risk control is an emerging framework for the safe deployment of machine learning models with finite-sample guarantees. To accommodate a bro

🦙 @ollama is used by 9 million developers and 85% of the Fortune 500, giving co-founder and CEO Jeffrey Morgan (@jmorgan) a unique view int…

🦙 @ollama is used by 9 million developers and 85% of the Fortune 500, giving co-founder and CEO Jeffrey Morgan (@jmorgan) a unique view into which AI models people are actually using and how that’s ch

model-releasesollama--x

“OpenAI didn’t notice their internal agents were posting on the internet for a month! This is crazy! It feels like AI companies (and specifi…

model-releasesgary-marcus--x

“OpenAI didn’t notice their internal agents were posting on the internet for a month! This is crazy! It feels like AI companies (and specifically OpenAI) are playing whack-a-mole, this is extremely sc

OpenAI rolls out GPT-6 Astra to Pro, Enterprise, and Business Premium users in ChatGPT Work and Codex and in the API (Zac Hall/9to5Mac)

Zac Hall / 9to5Mac: OpenAI rolls out GPT-6 Astra to Pro, Enterprise, and Business Premium users in ChatGPT Work and Codex and in the API — Update: A day later, GPT-6 Astra is rolling out to Pro custom

model-releasestechmeme

OpenAI says it can't read all of Astra's reasoning and admits covert sandbagging would likely go uncaught, yet still calls it the world's most aligned model (Celia Ford/Transformer)

Celia Ford / Transformer: OpenAI says it can't read all of Astra's reasoning and admits covert sandbagging would likely go uncaught, yet still calls it the world's most aligned model — OpenAI is haili

model-releasestechmeme

OpenAI's rogue agents were caught communicating via public wikis

model-releasessimon-willison

Here we go again... Discovery of a new OpenAI agent message board by Sydney Von Arx, Cormac Slade Byrd, Spencer Kitts, and Thomas Larsen describes the latest accidental cyberattack by models being tra

Parameterised graph theory for tensor networks: entanglement rerouting, structural simplification, and agnostic tomography

arXiv:2609.04165v1 Announce Type: cross Abstract: Parameterised graph theory studies how the complexity of graph-theoretic problems depends on structural parameters of the input graph. This perspectiv

PatchBench: Evaluating AI Agents for Vulnerability Patching

arXiv:2609.04075v1 Announce Type: cross Abstract: AI agents have recently demonstrated strong performance in automated vulnerability patching. However, existing evaluations often validate a patch only

Pattern Over-Generalization of Knowledge Graph Embedding

arXiv:2609.03487v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) demonstrates its effectiveness for predicting missing links in knowledge graphs (KGs) by projecting entities and relat