Search: “reasoning”

MOF-VERIFY: A Failure-Aware Agentic Harness for MOF Hypothesis Verification

arXiv:2610.03056v1 Announce Type: new Abstract: Large language models are increasingly used as reasoning components in AI-driven materials Co-Scientists, yet the reliability of the resulting verificat

5 Oct 2026

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Research

The Percept-V Challenge: Can Multimodal LLMs Crack Simple Perception Problems?

DGX agent

arXiv:2508.21143v4 Announce Type: replace Abstract: Cognitive science research treats visual perception, the ability to understand and make sense of a visual input, as one of the early developmental s

researcharxiv-cs-cl

5 Oct 2026

Beyond Final Accuracy: Auditing Communication in LLM Multi-Agent Systems

arXiv:2610.01042v1 Announce Type: new Abstract: Multi-agent communication aims to help agents benefit from one another's information. Yet improvements in system performance leave a fundamental ambigui

CARM: Cancellation-Aware Response Masking for LLM Reinforcement Learning

arXiv:2610.02039v1 Announce Type: cross Abstract: Recent years have witnessed the rapid adoption of reinforcement learning (RL) in large language model (LLM) post-training, with substantial gains in m

Closing the Loop: Practical Training Recipes for Looped Language Models

arXiv:2610.00673v1 Announce Type: cross Abstract: Looped language models increase effective depth by repeatedly applying a shared block of layers, but existing large-scale recipes require multi-stage

On Language Drift during RLVR Post-Training

arXiv:2610.02015v1 Announce Type: cross Abstract: Recent advances in LLM reasoning models---driven primarily by the paradigm of post-training via reinforcement learning with verifiable reward (RLVR)--

Permutation-Robust Decision Modeling with Candidate-Independent Block-Causal Attention

arXiv:2610.01601v1 Announce Type: cross Abstract: Decision models often score a variable-sized set of candidate actions encoded in a single sequence. This setting is increasingly relevant for System 1

The models are not trying to escape. They are trying to finish the task.

Something keeps happening in frontier AI, and the explanation we are given is always one size larger than the event. An OpenAI research model, running in a supposedly offline training environment, hit

model-releasesr-chatgpt

Towards Reliable Vision-Language Models for Autonomous Driving

arXiv:2610.01531v1 Announce Type: new Abstract: Vision-Language models (VLMs) are increasingly being explored in autonomous driving for tasks such as scene understanding, driving reasoning, decision-m

What Do Rationales Communicate? A Message-Intervention Study in Role-Specialized QA

arXiv:2610.00018v1 Announce Type: new Abstract: Role-specialized QA pipelines increasingly pass rationales from a reasoner to a verifier, but it is unclear what this message actually buys: better answ

EngramBench: A Capability-Grounded Benchmark for Skill-Evolution Harnesses

arXiv:2609.39284v1 Announce Type: cross Abstract: While large language models have achieved remarkable success in isolated code generation, authentic software engineering requires sustained reasoning,

Mitigating the Length-Scaling Tax with Online Distillation

arXiv:2609.38854v1 Announce Type: cross Abstract: Length scaling during reinforcement-learning (RL) post-training is often viewed as a sign of improved reasoning ability, especially on difficult probl

MM-FinEval: A Multi-Task Multimodal Benchmark for Real-World Financial Forecasting

arXiv:2609.38523v1 Announce Type: cross Abstract: Financial forecasting from earnings conference calls requires models to reason over complex corporate disclosures, market expectations, and subtle com

OpenJev-RLCD: A Working RLCD Implementation

arXiv:2609.38850v1 Announce Type: new Abstract: Decision models such as Jev answer questions with probabilities, which are only useful if they are calibrated. Open-source reproductions rely on supervi

Personalized State-Transition-Aware Memory for Clinical Agents

arXiv:2609.38490v1 Announce Type: cross Abstract: Large language model (LLM) agents that reason over clinical records must track changes in a patient's state while preserving the history needed to und

Semifactual Credit-Augmented Policy Optimization

arXiv:2609.40360v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has improved the reasoning capabilities of large language models (LLMs), yet their predictions r

TRACE: Trajectory Selection for Parallel Scaling of Search Agents

arXiv:2609.39912v1 Announce Type: cross Abstract: Parallel search may generate a correct answer that final-answer voting fails to select. We formulate this consolidation stage as trajectory selection

agentsarxiv-cs-ai

What Was Said, Not What Was 'Thought': Type-6 Logic for CoT Verification

arXiv:2609.38420v1 Announce Type: cross Abstract: We introduce Type-6 logic, a variant of dynamic epistemic logic augmented with two operators (uncertainty and recurrence), designed to model the infer

WorldAuditBench: Interactive 3D World Auditing with Multimodal Agents

arXiv:2609.40325v1 Announce Type: new Abstract: As interactive 3D worlds are increasingly used to study intelligent behavior, it becomes important to develop efficient pipelines for identifying anomal

FocusVTC: Efficient and High-Performance Visual Text Compression with Adaptive Resolution

arXiv:2609.36651v1 Announce Type: cross Abstract: Long-context reasoning in large language models incurs substantial computation and memory costs. Visual text compression (VTC) reduces input length by

local-aiarxiv-cs-ai

30 Sept 2026

Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering

arXiv:2609.38177v1 Announce Type: cross Abstract: Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs h

researcharxiv-cs-cl

30 Sept 2026

Towards Better Training Signal: Advantage Clipped Policy Optimization

arXiv:2609.36816v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a cornerstone for improving the reasoning capabilities of large language models (LLMs), but the need for on-polic

safetyarxiv-cs-lg

30 Sept 2026

ReVA: A Scene-Centric Dataset Beyond Repetition for Remote Sensing Video Question Answering

model-releasesarxiv-cs-cv

arXiv:2609.35507v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable advances in remote sensing. However, existing remote sensing multimodal reasoning

29 Sept 2026

Accidental discovery? or known method i'm missig? - Q's on compiling in sparse engrams and ideas swimming in my head

I set out to test portable Engrams and accidentally ended up testing compiled external memory instead. Am I onto something useful or reinventing a known idea? I've been building a small open research

local-air-localllama

25 Sept 2026

Watched my LLM router burn $11 on a 3-word prompt. Here's the fix.

I run a personal always-on agent fleet — eight seats claiming work in parallel from a shared task board, routing across Anthropic, OpenAI, xAI, Google, and a local Ollama floor. This week the spend fo

model-releasesr-ollama

25 Sept 2026

Agentic Governance and Adversarial Verification for Policy-Constrained LLM Healthcare Appeal Generation

arXiv:2609.27844v1 Announce Type: new Abstract: Claim denial management costs U.S. healthcare approximately $260 billion annually in administrative overhead. Large Language Models (LLMs) and Retrieval

local-aiarxiv-cs-ai

AlloyDB delivers PostgreSQL for agents: Real-time data at agent scale, with full workload isolation

Enterprises rely on mission-critical operational databases where performance slowdowns simply aren’t an option. Yet when even a few agents execute dense reasoning loops, the unpredictable surge in que

safetygoogle-cloud-ai

model : add Ling 3.0 VL support by aetherbird · Pull Request #29151 · ggml-org/llama.cpp

model-releasesr-localllama

Model Overview Ling-3.0-flash-VL inherits the language, reasoning, and long-context capabilities of Ling-3.0-flash, while extending them with native image and video understanding. The model has 124B t

Reachable Global Optimization in AI Systems: How Global Is Global?

arXiv:2609.27855v1 Announce Type: new Abstract: AI systems increasingly claim to optimize prompts, policies, architectures, plans, tool-use trajectories, reasoning traces, and test-time computation. T

ProcessLight: Process Supervision for Large Language Model Based Traffic Signal Control

arXiv:2609.22746v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently been introduced into traffic signal control (TSC) as decision agents due to their strengths in human-readable

23 Sept 2026

Implicit Rule Induction with Test-Time Task Embeddings in ARC-like Tasks

arXiv:2609.21181v1 Announce Type: new Abstract: The Abstraction and Reasoning Corpus and related benchmarks evaluate whether AI models can solve novel reasoning tasks, but often leave unclear whether

21 Sept 2026

b11057

model-releasesllama-cpp-releases

chat : add dedicated Ling 3.0 (Bailing V3) parser (#28682) chat: add dedicated Ling 3.0 (Bailing V3) parser Ling 3.0 Flash templates pre-open the think block in the generation prompt, so the model nev

20 Sept 2026

AI and Human Approaches to Mathematical Problem Solving

arXiv:2609.17779v1 Announce Type: cross Abstract: AI systems have begun to report solutions, disproofs, and substantive advances on long-standing mathematical problems, raising questions about whether

17 Sept 2026

Code Consistency Preference Optimization Verification for Language Model Alignment

model-releasesarxiv-cs-cl

arXiv:2609.19002v1 Announce Type: cross Abstract: Execution-based verification enhances large language models' mathematical reasoning through computational soundness and dependency-aware filtering. Ho

17 Sept 2026

The Mirage of Calibrated Confidence: Trajectory-Independence of Verbalized Confidence in Vision-Language Models

arXiv:2609.18453v1 Announce Type: new Abstract: A calibrated Vision-Language Model (VLM) can repeatedly self-correct, say 'Wait, I should recheck,' arrive at the wrong answer, and still report high co

17 Sept 2026

Autoformalizing Argumentative Material Inferences

arXiv:2609.16991v1 Announce Type: new Abstract: Natural language arguments are compelling before they are formally explicit. A premise supports a claim through defeasible warrants, background commitme

researcharxiv-cs-cl

Can We Do Interpretable NLI with Graphs Based on Atomic Propositions?

arXiv:2609.16814v1 Announce Type: new Abstract: While Large Language Model (LLM)-based Natural Language Inference (NLI) systems achieve high accuracy, their decision-making processes lack auditable st

OPD-Aha: From Linguistic Momentum to Visual Reflection in Multimodal On-Policy Distillation

arXiv:2609.16459v1 Announce Type: cross Abstract: Privileged on-policy distillation improves multimodal reasoning by allowing a teacher to evaluate student trajectories using rich, training-only visua

Right Direction, Wrong Step: Geometric Analysis of Finite-Step Failure in Looped Transformers

arXiv:2609.16665v1 Announce Type: cross Abstract: Looped Transformers offer a parameter-efficient route to test-time scaling by reusing shared layers for iterative latent reasoning. However, additiona

sensVLA: Spatially-Grounded Vision-Language-Action Model for Autonomous Wheel Loader

arXiv:2609.17021v1 Announce Type: new Abstract: Autonomous wheel-loader control requires joint reasoning over task semantics, egocentric vision, proprioception, and 3D scene geometry. We present sensV

agentsarxiv-cs-cv

Automating Attack Graph Construction for Agentic Pentesting. Towards Neuro-Symbolic Vulnerability Hunting

arXiv:2609.15523v1 Announce Type: cross Abstract: Logic attack graphs grounded in scanner output provide explicit and auditable attack path reasoning LLM-based agents lack. Integrating symbolic framew

agentsarxiv-cs-ai

Building Legal Reward Models for Grounding and Abstention

arXiv:2609.14739v1 Announce Type: cross Abstract: Large language models are increasingly used in high-stakes domains such as law, where systems must ground their reasoning in retrieved evidence and ab

Bypass Observation: A Conceptual Design of a Non-Intrusive Layer-Wise Semantic Extraction Architecture

arXiv:2609.13807v1 Announce Type: new Abstract: Large language models reason in high-dimensional hidden-state spaces, while users observe only final outputs. We introduce Bypass Observation, a non-int

Discovery Foundation Models: Toward Open-Ended Discovery Intelligence

arXiv:2609.15973v1 Announce Type: new Abstract: Foundation models have progressed from learning and reasoning over existing knowledge, to increasingly learning through action, tool use, and outcome fe

agentsarxiv-cs-cl

EMR: Self-Evolving Medical Multi-Agent System via Experience Mining and Reuse

arXiv:2609.15161v1 Announce Type: cross Abstract: Large language model (LLM) driven multi-agent systems have shown promise in complex clinical reasoning, yet existing approaches rely on static strateg

agentsarxiv-cs-ai

Tutorials

From Token Probabilities to Semantic Constraints: Towards Declarative Probabilistic Evaluation of Language Models

arXiv:2609.13520v1 Announce Type: new Abstract: While Large Language Models have improved rapidly, many fundamental questions remain about how to evaluate the knowledge and reasoning abilities they ac

tutorialsarxiv-cs-cl

The Theory of Mind Utility: A Formal Account of Mentalizing

arXiv:2606.12721v3 Announce Type: replace Abstract: Inferring another person's beliefs requires reconstructing their information access history: what they encountered, in what order, from whom, and wi

local-aiarxiv-cs-ai

HypoKG: Evidence-Disciplined Biomedical Hypothesis Generation Beyond Endpoint Knowledge