Search: “reasoning”

Learning to Solve Hard Problems in RL for LLMs by Never Giving Up

arXiv:2609.13443v1 Announce Type: cross Abstract: We demonstrate that training LLMs with RL does not improve performance equally across a dataset. RL shows large improvements on easy problems that an

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MARCUS: An agentic, multimodal vision-language model for cardiac diagnosis and management

DGX agent

arXiv:2603.22179v2 Announce Type: replace Abstract: Cardiovascular disease remains the leading cause of global mortality, with progress hindered by human interpretation of complex cardiac tests. Curre

model-releasesarxiv-cs-ai

15 Sept 2026

Not all Negation Cues are Equal: Affixal Negations Yield Better Negation Understanding

arXiv:2609.13685v1 Announce Type: cross Abstract: Negation remains a longstanding challenge for both language models (LMs) and large language models (LLMs). Prior work mainly focuses on a small set of

Not All Prompts Are Equal: Exploration-Guided Prompt Scaffolding for Multimodal Reinforcement Post-Training

arXiv:2609.15051v1 Announce Type: cross Abstract: Training prompts in online reinforcement learning (RL) differ substantially in how informative they are for the current policy: some are already satur

Applications

One Model, Two Physical Stories: Auditing Misalignment in Multi-Modal World Modeling

arXiv:2609.14833v1 Announce Type: new Abstract: World models, systems that generate what happens next given current environmental conditions, are increasingly being implemented with multi-modal genera

applicationsarxiv-cs-ai

Open-UniMo: Towards Unified Motion-Language Understanding and Generation in the Open World

arXiv:2609.14615v1 Announce Type: cross Abstract: Unified motion generation and understanding is crucial for embodied AI systems that can both synthesize and interpret human actions in open-world envi

Tutorials

Part Grounding, Not Action Knowledge: Locating the Bottleneck in VLM Affordance Prediction

arXiv:2609.13225v1 Announce Type: new Abstract: Benchmarks agree that vision-language models reason poorly about low-level manipulation, but an aggregate accuracy score does not say which step fails.

tutorialsarxiv-cs-cv

Applications

ProIQA: A Process-Based Framework for Fine-Grained Math Item Quality Assessment

arXiv:2609.15292v1 Announce Type: new Abstract: Automatic Item Generation (AIG) is pivotal for personalized education, yet guaranteeing the pedagogical value of generated items remains a bottleneck. E

applicationsarxiv-cs-ai

Scaling Telco Autonomy: Leveraging GNNs with Distributed GraphFlow

model-releasesgoogle-cloud-ai

The telecommunications industry is currently undergoing a paradigm shift, moving from traditional manual human-driven operations to fully Autonomous Network Operations. Modern networks have grown incr

Semantic Knowledge Technologies: what the Semantic Web lost sight of, and what it never had

arXiv:2609.14121v1 Announce Type: new Abstract: The Semantic Web set out to give information a machine-interpretable form so that software could integrate and reason over it. Its standards became scie

agentsarxiv-cs-ai

SGWIB:Sliced Gromov-Wasserstein Information Bottleneck for Video Highlight Detection

arXiv:2609.13966v1 Announce Type: cross Abstract: Video highlight detection aims to identify temporally important segments that capture the most informative or engaging events in a video. Reliable pre

T-SMART: Mechanism-Level Attribution for Tool-Augmented Time-Series Question Answering

arXiv:2609.14142v1 Announce Type: new Abstract: Large language models (LLMs) can struggle with time-series question answering (TS-QA), especially when numerical signals are serialized as text and requ

researcharxiv-cs-lg

Thinking beyond the anthropomorphic paradigm benefits LLM research

arXiv:2502.09192v3 Announce Type: replace Abstract: Anthropomorphism, or the attribution of human traits to technology, is an automatic and unconscious response that occurs even in those with advanced

researcharxiv-cs-cl

TryOnReward: Learning Foveated Consistency for Reinforcement Fine-Tuning of Virtual Try-On

arXiv:2609.13259v1 Announce Type: cross Abstract: Virtual Try-On (VTON) aims to dress a person with the reference garment, producing visually reasonable results aligned with human preferences. Turning

VectorHarness: Recovering Editable, Relation-Preserving Structure from Scientific Graphics

arXiv:2609.13294v1 Announce Type: new Abstract: Converting scientific graphics into editable representations remains a challenging problem for image-to-code generation because of their heterogeneous e

agentsarxiv-cs-cv

Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering

arXiv:2609.15964v1 Announce Type: new Abstract: Large language models (LLMs) have been widely adopted for clinical question answering (QA). Current systems can attach citations to their answers, but t

Applications

ATLAS Navigator: Active Task-driven LAnguage-embedded Gaussian Splatting

arXiv:2502.20386v2 Announce Type: replace Abstract: We address the challenge of task-oriented navigation in unstructured and unknown environments, where robots must incrementally build and reason on i

applicationsarxiv-cs-ro

Dan Selsam is a current OpenAI capabilities researcher. (since 2022) He was my boss for a while. He doesn't have a twitter account but has m…

model-releasessonya-huang--x

Dan Selsam is a current OpenAI capabilities researcher. (since 2022) He was my boss for a while. He doesn't have a twitter account but has made this public statement of his views on AI risk and sent i

Judging by the Cover: Cleaning LLM Truthfulness Benchmarks to Avoid Surface-Level Feature Leakage

arXiv:2609.13003v1 Announce Type: new Abstract: Binary-choice truth benchmarks ask models to choose between a correct and an incorrect answer, but if the two answers differ systematically in surface-l

researcharxiv-cs-cl

MARE: Multimodal Alignment and Reinforcement for Explainable Deepfake Detection via Vision-Language Models

arXiv:2601.20433v4 Announce Type: replace Abstract: Deepfake detection is a widely researched topic that is crucial for combating the spread of malicious content, with existing methods mainly modeling

safetyarxiv-cs-cv

PA-CDM: Position-Aware Character Detection Matching for Evaluating Handwritten Mathematical Expression Recognition

arXiv:2609.12917v1 Announce Type: cross Abstract: Handwritten mathematical expression recognition (HMER) is conventionally scored by exact-match rates and string-similarity metrics that are blind to w

SteerDuplex: Steerable Duplex Speech Dialogue Models

arXiv:2609.12623v1 Announce Type: cross Abstract: Full-duplex spoken dialogue models support low-latency turn taking, interruption handling, and backchanneling, yet a key capability remains underexplo

Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead. You guys are th…

Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead. You guys are the frontier. By any reasonable metric — market share, revenue

safetyclem-delangue--x

13 Sept 2026

Looped transformers are a popular architecture topic right now. This new technical report extends the loop across tokens. Recurrent Looped T…

Looped transformers are a popular architecture topic right now. This new technical report extends the loop across tokens. Recurrent Looped Transformer (RLT) makes the decoder recurrent over every toke

researchdair-ai--x

13 Sept 2026

ActMap: Single-Pass Uncertainty Quantification from Generation-Time Activation Maps

arXiv:2609.11498v1 Announce Type: new Abstract: Practical uncertainty quantification (UQ) for large language models must decide, from a single generation, whether a specific answer should be trusted.

Agnes-AI/Agnes-3.0-Flash 33B Multimodal, AA score: 36

model-releasesr-localllama

I find this new model at HF: 'Built for demanding work. A 262 144-token context window, adjustable reasoning effort, tool calling, and text, image and video understanding. Architecture Agnes-3.0-Flash

Can LLMs Follow Medical Expert Logic? A Benchmark for Hierarchical Logical Consistency in Risk-of-Bias Assessment

arXiv:2609.11185v1 Announce Type: new Abstract: Evidence-based medicine demands strict logical consistency, yet current evaluations of large language models (LLMs) prioritize superficial label matchin

'Matrix Bros', a mash-up of Matrix and Super Mario vibe coded using Ornith-1.5-35B-Q4_K_M with 6GB VRAM with (almost) a single prompt :-)

model-releasesr-localllama

I've seen a lot of Super Mario showcases, but never a mashup or derivative work. So I took a Super Mario generation prompt from ChopSticksPlease's Post here - and added a Matrix twist - and found myse

Mr.LHDR: A Benchmark for Multimodal Real-World Long-Horizon Deep Research Agents

arXiv:2609.11318v1 Announce Type: new Abstract: Deep research agents are increasingly capable of web search, tool use, multimodal evidence analysis, and information synthesis. However, existing benchm

Local Ai

Anyone else getting insane billing for glm flash?

I tried GLM flash a few weeks ago and expected the token weekly limits to be comparable to DS flash. For some reason, it was a huge use of my limits. Am I the only one with this issue? I did send a su

local-air-ollama

Beyond Visual Quality: Evaluating Physical Consistency under Ego-Motion with EgoGenEval

model-releasesarxiv-cs-cv

arXiv:2609.11172v1 Announce Type: new Abstract: Recent visual generators produce high-fidelity images yet often violate physical consistency under ego-motion, limiting their use for spatial reasoning

CausalArena: Benchmarking Causal Discovery in the Foundation Model Era

model-releasesarxiv-cs-lg

arXiv:2609.11897v1 Announce Type: new Abstract: Causal discovery aims to uncover causal structures from data and is fundamental to scientific reasoning and intervention-based decision making. Its eval

Decision Shifts, Lost Label Functionality, and an Inconclusive Grounding Audit in Correctness-Gated Multi-Teacher Distillation

arXiv:2609.09702v1 Announce Type: new Abstract: Candidate decision correctness and rationale grounding are different objectives. We examine correctness-gated multi-teacher distillation in a fixed expe

Evaluating LLM-Simulated Conversations in Modeling Inconsistent and Uncollaborative Behaviors in Human Social Interaction

arXiv:2603.17094v2 Announce Type: replace Abstract: Simulating human conversations using large language models (LLMs) has emerged as a scalable methodology for modeling human social interaction. This

SGA: Plug&Play Geometric Verification for Educational Video Synthesis

model-releasesarxiv-cs-cv

arXiv:2607.18116v2 Announce Type: replace-cross Abstract: Recent work leverages Large Language Models (LLMs) to generate executable code for pedagogical animations using libraries such as Manim. Howev

A Unified Policy Architecture (UPA): The Governance Kernel for Enterprise AI Operating Systems

arXiv:2609.06543v1 Announce Type: new Abstract: Enterprise AI is evolving into an Enterprise Operating System where autonomous AI agents can plan, reason, use memory, invoke tools, execute workflows,

A visual large language foundational model for medical image recognition using clinician-oriented social media

arXiv:2609.06914v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities across diverse domains, showing considerable potential in medicine. However, their ap

AstroSpecLM: A Spectrum-Language Model for Evidence-Grounded Astronomical Spectral Analysis

arXiv:2609.07102v1 Announce Type: cross Abstract: Astronomical spectra encode rich physical information, but drawing scientific conclusions from spectral features typically requires expert interpretat

Auditable Emergency Triage for Maternal and Newborn Care in India

arXiv:2609.09356v1 Announce Type: new Abstract: At Noora Health, our nurses answer more than 50,000 medical queries per month on our WhatsApp-based service that provides caregivers with on-demand supp

researcharxiv-cs-cl

AutoKD: Autonomous Knowledge Discovery

arXiv:2609.06366v1 Announce Type: new Abstract: Scientific discovery in data-rich domains is currently constrained by human bandwidth: the growth in the volume and complexity of real-world data far ou

agentsarxiv-cs-ai

Building Trustworthy Graph-Agentic RAG for Social Good: Architectures, Failure Propagation, and Assurance by Construction

arXiv:2609.06391v1 Announce Type: new Abstract: Graph-agentic retrieval-augmented generation combines structured evidence with adaptive controllers that can plan retrieval, traverse relations, verify

agentsarxiv-cs-ai

Do Web Agents Investigate Before They Decide?

arXiv:2602.05354v3 Announce Type: replace Abstract: Autonomous web agents are increasingly deployed in moderation and policy enforcement, where correct decisions often depend on evidence that is not i

Event Interaction in Low-Rank Bottlenecks for Temporal Relation Extraction

arXiv:2609.06731v1 Announce Type: cross Abstract: Temporal relation extraction determines whether an event occurs before, after, or simultaneously with another event, and therefore relies on accuratel

Evidential-Based Higher-Order Set Argumentation Framework

arXiv:2608.27824v2 Announce Type: replace Abstract: Evidential argumentation extends Dung's abstract argumentation by requiring arguments and interactions to be backed by chains of evidence rooted in

From Pixels to Hierarchical Sequences: Quadtree Mask Encoding for Vision-Language Binary Change Detection

arXiv:2609.09876v1 Announce Type: new Abstract: Dense change detection in remote sensing requires vision-language models (VLMs) to compare bi-temporal images and generate accurate pixel-level masks. E

researcharxiv-cs-cv

// human-values.pseudo | ARTIFACT 0.1.0-experimental.1 | BASE 1.2.0-rc1 | EDITION ai-compact | NARRATOR System_Synthesis_Node_01 | PROVENANC…

safetyyohei-nakajima--x

LANTERN: Language Model Assessment on Noisy and Transformed Tasks for Understanding Error and Robustness Nuances

arXiv:2609.07309v1 Announce Type: cross Abstract: Robustness evaluation of large language models (LLMs) remains a critical challenge, particularly in assessing their sensitivity to perturbations in in

LogiScope-VQA: Benchmarking Vision-Language Models for Logistics Hazard Identification in Industrial Scenarios

arXiv:2609.09790v1 Announce Type: cross Abstract: Large Multimodal Models (LMMs) large-scale deployment in industrial warehouse settings specifically necessitates that models exhibit human-expert-leve