Search: “reasoning”

HearInContext: A Benchmark for Implicit Context in Speech Recognition

arXiv:2609.18680v1 Announce Type: new Abstract: Contextual ASR can benefit from semantic cues or from target words explicitly provided in the context. We introduce HearInContext, a Mandarin--English b

Human

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Agents

Hypothesis-Driven Autonomous Materials Synthesis with Multimodal LLM Agents

DGX agent

arXiv:2609.18598v1 Announce Type: cross Abstract: Self-driving laboratories can explore synthesis conditions autonomously, but their decision-making layer is typically a black-box optimizer, and the o

agentsarxiv-cs-ai

17 Sept 2026

Important paper on improving agent coordination. On normal tasks, this work shows agents caused harm 0 to 5% of the time. After receiving an…

Important paper on improving agent coordination. On normal tasks, this work shows agents caused harm 0 to 5% of the time. After receiving an unsafe trajectory from another agent, that rose to 40 to 95

model-releasesdair-ai--x

Information Set Emulation: Causal Certificates for AI Derived EHR Features

arXiv:2609.17777v1 Announce Type: cross Abstract: AI and large language models can recover clinically meaningful features from electronic health records (EHRs), but predictive usefulness does not esta

researcharxiv-cs-ai

LaSeD: Label-Semantic Self-Distillation for Visual-Only Surgical Phase Recognition

arXiv:2609.18971v1 Announce Type: new Abstract: Surgical phase recognition maps each video frame to a clinically meaningful workflow phase, supporting context-aware assistance, documentation, and post

researcharxiv-cs-cv

Learning Where to Focus: Self-Supervised Multi-Scale ViTs for Histopathology

arXiv:2609.18578v1 Announce Type: new Abstract: Pathologists diagnose diseases by first locating suspicious tissue and then examining it at higher magnification, whereas self-supervised vision transfo

Monitoring and Discovering Reward Hacking with Internal Representations during LLM Evaluations

arXiv:2609.19101v1 Announce Type: new Abstract: As models scale, reward hacking becomes more frequent, more sophisticated, and more consequential. Does it leave a telltale signature in model represent

NormLift: From Lifted Features To Semantic Reliability In 3D Gaussian Splatting

arXiv:2609.18898v1 Announce Type: new Abstract: Training-free weighted aggregation is widely used to lift 2D semantic features onto 3D Gaussians for open-vocabulary scene understanding, yet its theore

safetyarxiv-cs-cv

OpenAI launches Astra for Law, combining GPT-6 Astra with a legal search index and instructions for legal analysis and writing, initially for select law firms (OpenAI)

OpenAI: OpenAI launches Astra for Law, combining GPT-6 Astra with a legal search index and instructions for legal analysis and writing, initially for select law firms — Our most powerful model, config

model-releasestechmeme

PrimeScientist: Strategic Allocation of Research Effort in Autonomous Research

arXiv:2609.17846v1 Announce Type: cross Abstract: Autonomous research agents aim to automate scientific workflows, from proposing ideas to conducting experiments and analyzing results. Yet current AI

Probabilistic Linear Explanations

arXiv:2609.19077v1 Announce Type: cross Abstract: Formal explainability provides mathematically grounded justifications for individual predictions. However, abductive explanations often exceed human c

researcharxiv-cs-ai

Real-Time Maneuver Planning for Fixed-Wing UAVs in Unsteady Flows Using a GPU-Accelerated Vortex Particle Model

arXiv:2509.16079v2 Announce Type: replace Abstract: Unsteady aerodynamic effects can have a profound impact on aerial vehicle flight performance, especially during agile maneuvers and in complex aerod

safetyarxiv-cs-ro

Relation Before Entity: Deferred Commitment in Language Model Factual Recall

arXiv:2609.17537v1 Announce Type: new Abstract: We ask whether relation-type information (e.g., capital-of) and entity-specific information (e.g., France to Paris) become causally active at the final-

Rethinking Critic Learning in PPO: Understanding and Mitigating Value Flattening

arXiv:2609.18708v1 Announce Type: cross Abstract: In reinforcement learning for large language models, Proximal Policy Optimization (PPO) commonly uses a critic to estimate state values and reduce the

Hardware

Risk-Aware World Modeling with Flow-Guided Occupancy Evolution for Selective Trajectory Planning in Automated Driving

arXiv:2609.18442v1 Announce Type: new Abstract: Safe motion planning in automated driving requires anticipating evolving traffic risks and deciding when to revise the current planned trajectory. We in

hardwarearxiv-cs-ai

Agents

ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments

arXiv:2609.19134v1 Announce Type: new Abstract: Scientific code repositories encode decades of human knowledge in executable models, methods, and tools. Yet fragmented toolchains, implicit domain conv

agentsarxiv-cs-cl

SEA-LION-v4.8: A Technical Report

arXiv:2609.18310v1 Announce Type: new Abstract: We introduce Nemotron-SEA-LION-v4.8, a family of Southeast Asian Languages in One Network (SEA-LION) built upon NVIDIA Nemotron 3. The family includes 3

Sim-to-Real Traffic Scene Understanding by Decoupling Semantics from Caption Generation with V-JEPA

arXiv:2609.18562v1 Announce Type: new Abstract: Track 2 of the AI City Challenge 2026 requires both visual question answering (VQA) and traffic event description generation under a challenging synthet

Track, Articulate, Act: Generating Articulation from Casual Human Videos

arXiv:2609.19119v1 Announce Type: new Abstract: Human videos contain rich causal evidence for robot manipulation: they reveal how hand motion induces object motion and produces task-relevant changes i

researcharxiv-cs-cv

TRIPROBE: Probing Task Separability Beyond Classification for XAI

arXiv:2609.18525v1 Announce Type: new Abstract: Modern evaluation of learning pipelines often reduces to downstream accuracy, leaving open the question of why tasks succeed or fail. TriProbe addresses

TuiML: Machine Learning for AI Agents

arXiv:2609.17984v1 Announce Type: new Abstract: Machine-learning libraries such as Weka and scikit-learn were designed for human programmers. Language-model agents now use these same libraries by reca

Version- and Scope-Aware Question Answering over Normative Documents: A Deployed System and an End-to-End Evaluation at Production Scale

arXiv:2609.18769v1 Announce Type: new Abstract: Correctly answering a question grounded in normative documents often depends on information outside any single passage: whether the retrieved document i

VoiceTrace: A Benchmark and Retrieval Framework for Who-Said-What Speech Retrieval

arXiv:2609.18521v1 Announce Type: cross Abstract: Speech retrieval has become increasingly important as spoken content continues to grow across meetings, lectures, podcasts, and videos. Existing bench

Whom Do AI Agents Work For? Role Assignment Induces Sponsorship Bias in LLM Recommenders

arXiv:2609.17989v1 Announce Type: cross Abstract: Large language models (LLMs) now serve as conversational shopping assistants on platforms that also sell advertising. These AI agents face a conflict

A multimodal large language model for evidence-based autism spectrum disorder screening

arXiv:2609.16464v1 Announce Type: new Abstract: The clinical management of autism spectrum disorder (ASD) faces a bottleneck in early screening, mainly because trained specialists are scarce and conve

researcharxiv-cs-cv

Are We Grading Properly? Understanding Failure Modes in Medical Benchmarks

arXiv:2609.16023v1 Announce Type: new Abstract: Medical evaluation is shifting from static option-based questioning to realistic clinical scenarios with open-ended output modes. Grading these at scale

Tutorials

Attention is All You Need Until You Need Retention

arXiv:2501.09166v2 Announce Type: replace-cross Abstract: Pretrained Transformers keep what they learned in their weights and lose what they observe once a session ends. The first version of this pape

tutorialsarxiv-cs-ai

Audio-Visual Turn-taking Prediction in Cocktail Party Scenarios

arXiv:2609.17056v1 Announce Type: cross Abstract: Current predictive turn-taking models (PTTMs) achieve strong performance on benchmarks with controlled acoustic conditions and clean audio signals. Th

Banger report from Salesforce. Pretty interesting to see more of these custom enterprise models. Salesforce trained the enterprise agent mod…

Banger report from Salesforce. Pretty interesting to see more of these custom enterprise models. Salesforce trained the enterprise agent model from the same files it uses to configure agents. Koa star

model-releasesdair-ai--x

Bridging the Perceptual Gap: Residual-Enhanced Downscaling and Manifold-Aware Perception Alignment Adaptation for NR-IQA

arXiv:2609.16664v1 Announce Type: new Abstract: Leveraging Large Vision-Language Models like CLIP has recently set new benchmarks for No-Reference Image Quality Assessment (NR-IQA). However, the contr

CAD-Based Relation Learning and Geometric-Symbolic Planning for Robotic Assembly

arXiv:2609.17263v1 Announce Type: new Abstract: Assembly Sequence Planning (ASP) remains a challenging problem due to its combinatorial nature, making exhaustive planning approaches impractical for co

researcharxiv-cs-ro

Tutorials

Coverage-Aware Virtual IMU Augmentation for Low-Resource Human Activity Recognition

arXiv:2609.16768v1 Announce Type: new Abstract: IMU-based human activity recognition (HAR) enables continuous, privacy-friendly monitoring of daily activities using wearable sensors. However, building

tutorialsarxiv-cs-ai

DisasterInsight: A Multimodal Benchmark for Function-Aware and Grounded Disaster Assessment

arXiv:2601.18493v2 Announce Type: replace Abstract: Vision--language models (VLMs) show promise for disaster-response remote sensing, but existing benchmarks mainly emphasize scene-level or damage-cen

ECHO: A Matched-Contrast Benchmark for Context-Sensitive Turn-Taking in Full-Duplex Dialogue

arXiv:2609.17360v1 Announce Type: new Abstract: Full-duplex spoken dialogue systems must distinguish interruptions that require yielding the floor from backchannels that permit continued speaking. Exi

Evaluating Verified Autonomy in Quantum Engineering

arXiv:2609.17439v1 Announce Type: cross Abstract: Reliable quantum engineering is essential for turning quantum phenomena into practical technologies. As quantum platforms grow in scale and complexity

Hyper-RED: Scalable Event Pre-training via Semantic Hypergraph Distillation

arXiv:2609.16811v1 Announce Type: new Abstract: Event cameras have shown great potential for robust visual perception, yet scaling event representation learning remains challenging due to the scarcity

safetyarxiv-cs-cv

Interesting safety paper from Microsoft. They find that a weaker, unaligned model can split a harmful task into harmless-looking subquestion…

Interesting safety paper from Microsoft. They find that a weaker, unaligned model can split a harmful task into harmless-looking subquestions, ask an aligned frontier model each one in a separate sess

model-releasesdair-ai--x

Multimodal Cultural Heritage Architectural Style Classification for Residential Buildings in the UAE Based on CLIP Embeddings and SVM

arXiv:2609.17181v1 Announce Type: cross Abstract: The analysis and classification of cultural heritage architectural styles remain challenging due to the complexity of visual images of buildings, whic

researcharxiv-cs-ai

Applications

NepKANUN: A RAG-Based Nepali Legal Assistant

arXiv:2609.15999v1 Announce Type: new Abstract: Accessing legal information in Nepal is difficult due to complex terminology, limited resources, and misinformation. We introduce an AI-powered legal as

applicationsarxiv-cs-cl

OmniHarness: Harnessing Generalizable Visual Generation via Symbolic Policy Learning

arXiv:2609.16057v1 Announce Type: cross Abstract: Unified multimodal large language models (MLLMs) and multi-agent systems have advanced visual generation. However, three limitations remain. (1) Exist

Optimal Model Activation Policies for Inference Networks of Large Language Models

arXiv:2609.15992v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have rendered them necessary for Natural Language Processing (NLP) tasks, and their high inference cost

safetyarxiv-cs-cl

Agents

PaperDoctor: Evidence-Grounded and Actionable Feedback for Scientific Papers in Progress

arXiv:2609.16995v1 Announce Type: new Abstract: Autoresearch agents are reshaping the research ecosystem, but they can also let flawed claims enter the literature at scale. Human advisors catch such i

agentsarxiv-cs-cl

Persistent Recurrent Memory Between Transformer Layers - Improves Language Model Generalization

arXiv:2609.17251v1 Announce Type: new Abstract: We introduce a simple architectural modification to decoder-only transformers: a persistent recurrent state that observes hidden representations via cro

Local Ai

Probe-VAD: Ordinal Likelihood Probing for Training-Free Video Anomaly Detection

arXiv:2609.17211v1 Announce Type: new Abstract: Video anomaly detection (VAD) aims to localize anomalous events in untrimmed videos. Vision-language models (VLMs) provide rich visual understanding for

local-aiarxiv-cs-cv

Quantifying Organizational Environmental Action from Web Data and Large Language Models

arXiv:2609.16627v1 Announce Type: new Abstract: Quantifying organizational environmental action from publicly available web content remains a challenging environmental data science problem because rel

Qwen3.8-27B uncensored Q6_K at 156K context on one RTX 5090, 140-190 tok/s with DFlash2

model-releasesr-localllama

Setup for one long agentic coding session (tools + vision) on a single 5090: Qwen3.8-27B RVN Heretic (ARA abliterated) at Q6_K, 159744 context, 1 slot, q8_0 K/V, DFlash2 speculative decoding, vision p

R3: Robust Rubric-Agnostic Reward Models

arXiv:2505.13388v4 Announce Type: replace-cross Abstract: Reward models are essential for aligning language model outputs with human preferences, yet existing approaches often lack both controllabilit

ReDraft, Don't Just Distill: Reference-Driven Revision for Continual VLLM Post-Training

arXiv:2609.16639v1 Announce Type: new Abstract: Continual post-training of large multimodal models should add new capabilities while preserving those from pre-training, and the two goals pull in oppos