Search: “reasoning”

arXiv:2610.20352v1 Announce Type: new Abstract: Multimodal Large Language Models have made significant progress in referring expression comprehension (REC), yet most REC benchmarks still focus on fina

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Test-Time Scaling via Budgeted Multi-Attribute Verification

DGX agent

arXiv:2609.34322v2 Announce Type: replace Abstract: Verifying LLM-generated answers under a shared computational budget requires jointly deciding which candidates to inspect and which verification att

tutorialsarxiv-cs-ai

15 Oct 2026

Typed Decision Models on Tabular Data

arXiv:2610.19536v1 Announce Type: new Abstract: Typed decision models are language models that answer a question with a fixed set of possible answers by returning a probability for each answer instead

researcharxiv-cs-cl

VASPO: Self-Distillation with Privileged Value Estimation

arXiv:2610.20516v1 Announce Type: new Abstract: On-policy self-distillation provides dense supervision for reasoning models via a privileged self-teacher. However, this supervision reflects local toke

safetyarxiv-cs-cl

What the Machine Invented: Mining New Mathematical Instruments from OpenAI's October 2026 Release of AI-Generated Mathematics

arXiv:2610.17090v1 Announce Type: cross Abstract: On 6 October 2026 OpenAI published an initial 722 AI-written mathematical manuscripts, organized into 372 problem families, in the public repository g

Which Knowledge Should LLMs Trust? Uncovering a Generalizable Steering Direction Across Knowledge Conflicts

arXiv:2610.20067v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently encounter conflicts between internal parametric knowledge and external contextual knowledge, yet the mechanisms

researcharxiv-cs-cl

Local Ai

Why Agentic Workflows Fail: A Taxonomy Derived from Literature and Empirical Data

arXiv:2610.17418v1 Announce Type: cross Abstract: Agentic workflows combine large language models with planning, memory, tools, execution environments, and iterative feedback. Their failures are diffi

local-aiarxiv-cs-ai

Tutorials

World Models Need a Physical Registry: Learning Internal Predictive States for Physically Plausible World Models

arXiv:2610.16365v1 Announce Type: new Abstract: Video world models must generate physically plausible futures, not just realistic frames. Existing approaches typically use semantic, physical, or predi

tutorialsarxiv-cs-ai

A Production-Grade, High-Efficiency Agentic RL Framework for Frontier LLMs with Validated Recipes

arXiv:2610.16352v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a critical phase in the post-training pipeline of large language models (LLMs). As the frontier of LLM capabi

Articulated 3D Scene Graphs for Open-World Mobile Manipulation

arXiv:2602.16356v2 Announce Type: replace-cross Abstract: Semantic scene understanding has enabled robots to reason and perform affordance-driven object interaction. Despite this, real-world manipulat

applicationsarxiv-cs-cv

Code2Worlds-2: Physically Plausible Agent Harness for Embodied World Simulation

arXiv:2610.17651v1 Announce Type: cross Abstract: Recent coding large language models (LLMs) can synthesize dynamic 4D worlds from natural language, but the resulting content remains a visual artifact

Local Ai

DyJR: Preserving Diversity in Reinforcement Learning with Verifiable Rewards via Dynamic Jensen-Shannon Replay

arXiv:2603.16157v2 Announce Type: replace Abstract: While Reinforcement Learning (RL) enhances Large Language Model reasoning, on-policy algorithms like GRPO are sample-inefficient as they discard pas

local-aiarxiv-cs-lg

From Classification to Cross-Modal Understanding: Leveraging Vision-Language Models for Fine-Grained Renal Pathology

arXiv:2511.11984v2 Announce Type: replace Abstract: Fine-grained glomerular subtyping is essential for kidney biopsy interpretation, yet it presents a harder setting than the broad organ- or disease-l

Is Complex Query Answering Really Complex?

arXiv:2410.12537v4 Announce Type: replace Abstract: Complex query answering (CQA) on knowledge graphs (KGs) is gaining momentum as a challenging reasoning task. In this paper, we show that the current

applicationsarxiv-cs-lg

Look Back to Move Forward: Learning to Revisit for Agentic Compositional Image Generation

arXiv:2610.16224v1 Announce Type: new Abstract: Text-to-image models have made remarkable progress in visual fidelity and instruction following, yet complex compositional generation remains challengin

Make {pi}0.5 Learn to Call Astra for Reliable Robot Manipulation

arXiv:2610.14117v1 Announce Type: new Abstract: GPT-6 Astra provides robust embodied reasoning, but frequent external queries increase inference time and token costs. We equip a frozen pi_{0.5} policy

safetyarxiv-cs-ro

METIS: Multi-Source Egocentric Training for Integrated Dexterous Vision-Language-Action Model

arXiv:2511.17366v2 Announce Type: replace-cross Abstract: Building a generalist robot that can perceive, reason, and act across diverse tasks remains an open challenge, especially for dexterous manipu

applicationsarxiv-cs-cv

Model-Based Online Decision Making via Generative Trajectory Planning

arXiv:2610.18677v1 Announce Type: new Abstract: Online decision-making faces a tension between efficient inference and long-horizon reasoning. Value-based methods rely on short-horizon bootstrapping t

PINT: A Unified Model with Shared Predictive Intent for Robot Manipulation

arXiv:2610.16355v1 Announce Type: new Abstract: Generalist robot manipulation can benefit from pretrained vision-language models (VLMs) for semantic reasoning and video generation models (VGMs) for wo

applicationsarxiv-cs-ro

Proactive Physical AI through Continuous Observation and Timely Intervention

arXiv:2610.16967v1 Announce Type: new Abstract: Physical AI is commonly formulated around an explicitly specified task: given a goal or instruction, a system perceives, reasons, and acts. In many real

applicationsarxiv-cs-cv

Probing and Inducing Clinical Modality Grounding in Brain Tumor Segmentation

arXiv:2603.19844v3 Announce Type: replace Abstract: Multimodal MRI provides complementary information for brain tumor segmentation, but high accuracy alone does not reveal whether a model relies on cl

Reward-Aligned Distillation

arXiv:2610.14572v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards improves the reasoning capabilities of large language models, but remains computationally expensive and s

Selective Successor Eligibility Traces for RLVR

arXiv:2605.05965v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a key approach for improving the reasoning abilities of large language models. Howe

SERF: Spatiotemporal Environment and Robot Feature Map for Long-Horizon Mobile Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.12956v2 Announce Type: replace Abstract: Long-horizon robot mobile manipulation requires continual reasoning about localization, environment changes, and task progress, all of which are cha

Soft Teacher Forcing

model-releasesarxiv-cs-lg

arXiv:2610.17189v1 Announce Type: cross Abstract: Soft tokens have so far been used to replace discrete chain-of-thought in latent reasoning methods. These approaches typically require multi-stage tra

Text-Vision Co-Instructed Image Editing

arXiv:2606.16767v2 Announce Type: replace Abstract: Existing image editing methods can be generally categorized into textual instruction-based and visual prompt-based ones. Textual instructions are se

Think Before You Speak: Enabling Training-Free Latent Communication Between Language Models

arXiv:2610.16165v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in solving complex tasks in coding, mathematical logic, and iterative reasoning

agentsarxiv-cs-lg

VideoEvoHarness: Self Evolving Agent Harness from Unlabeled Videos for Video Understanding

arXiv:2610.15389v1 Announce Type: new Abstract: Video understanding agents rely on a harness to acquire evidence, use tools, and reason, but improving it requires substantial effort. Recent self evolu

A Critical Look at Power Sampling when Test Time Sharpening LLMs

arXiv:2610.13653v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has substantially improved LLM reasoning, yet growing evidence suggests it mainly performs distr

researcharxiv-cs-lg

Competence-Aware Orchestration for LLM-Based Multi-Agent Systems

arXiv:2610.13144v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have emerged as a promising paradigm for enhancing complex reasoning through role specialization and collaboration,

agentsarxiv-cs-ai

How Reliable are AMR Parser Outputs? Uncertainty Estimation for AMR Parsing

arXiv:2610.13236v1 Announce Type: cross Abstract: Recent advances have significantly improved the performance of Abstract Meaning Representation (AMR) parsers, yet determining when their outputs can b

Mind the Temporal Gap: Evaluating Video Models for Temporal Understanding in Driving

arXiv:2610.12575v1 Announce Type: cross Abstract: Modern video-language models are increasingly treated as general-purpose video reasoners, yet it remains unclear whether they robustly capture tempora

safetyarxiv-cs-ro

PACT: Privileged Trace Co-Training for Multi-Turn Tool-Use Agents

arXiv:2606.16215v2 Announce Type: replace-cross Abstract: Multi-turn tool-use agents must reason, call tools, and adapt to observations across several interaction turns. Post-training such agents is c

agentsarxiv-cs-ai

Rollout-Time Intervention: Unlocking Agentic Reinforcement Learning Beyond Policy Limits

arXiv:2610.13438v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a key paradigm for improving large language model (LLM) agents, enabling stronger reasoning, planning, and to

safetyarxiv-cs-ai

SpireBench: Evaluating Long-Horizon Strategic Play of Agentic Models with Slay the Spire

model-releasesarxiv-cs-ai

arXiv:2610.12596v1 Announce Type: new Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short a

TreeHCA: Hindsight-Guided Exploration and Credit Assignment for Multi-Turn LLM Agents

model-releasesarxiv-cs-lg

arXiv:2610.12828v1 Announce Type: new Abstract: Outcome-supervised group-relative policy optimization (GRPO) assigns the same advantage to every token in an LLM agent trajectory, leaving useful and un

VLMs are Native Action Models: Unleashing the Manipulation Capabilities of VLMs with Explicit Action-Space Grounding

arXiv:2610.12832v1 Announce Type: new Abstract: Pretrained vision-language models (VLMs) already exhibit strong visual, spatial and reasoning capabilities relevant to robotic manipulation. The key cha

safetyarxiv-cs-ro

zip2zip++: Towards Inference-Time Token Compression with Minimal Quality Loss

arXiv:2610.13605v1 Announce Type: new Abstract: Dynamic vocabularies built on-the-fly via Lempel-Ziv-Welch (LZW) compression let a language model represent the same text in fewer tokens, but prior wor

researcharxiv-cs-cl

How to make gemma 4 works with SWEBench?

model-releasesr-localllama

I wanted to compare gemma 4 31b qat q4 and qwen3.8 27b iq4_nl, so I run SWEBench verfied on them. The original gemma 4 chat template doesn't work with preserve reasoning, so google released an update

10 Oct 2026

I asked 3 Qwen 3.8 models to solve recent AtCoder problems at 4 thinking efforts

model-releasesr-localllama

I was looking into finalizing my daily driver and it was not clear which one to chose. I have a 5060ti 16GB so I picked the following contenders, which seem to be working at a reasonable speed on my h

10 Oct 2026

Complexity of Grounded Semantics and Preferred Semantics in Finitary Argumentation Frameworks

arXiv:2610.12008v1 Announce Type: new Abstract: Abstract argumentation frameworks (AFs) introduced by Dung provide a formal foundation for non-monotonic reasoning in artificial intelligence. While dec

DuplexAgent-RSI: Recursive Harness Improvement for Full-Duplex Voice Agent Collaboration

arXiv:2610.11299v1 Announce Type: new Abstract: Voice agents are converging on a collaboration pattern: a full-duplex interaction model stays on the live channel as the entry to the conversation, whil

agentsarxiv-cs-ai

Learning from Own Solutions: Self-Conditioned Credit Assignment for Reinforcement Learning with Verifiable Rewards

arXiv:2606.18810v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has driven substantial progress in training LLMs for reasoning tasks, but representative

safetyarxiv-cs-ai

Learning Probabilistic Logic Programs with Functional Gradient Guided Language Models

arXiv:2610.12303v1 Announce Type: new Abstract: Declarative logic programs offer a powerful and interpretable abstraction for encoding relational structure and neurosymbolic reasoning, by expressing d

OmniCapBench: A Deep-Structured Evaluation Framework for Fine-Grained Audio-Visual Captioning

arXiv:2610.12458v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are rapidly evolving toward continuous audio--visual reasoning, creating an urgent need for evaluations that ex

$OneMillion-Bench: How Far are Language Agents from Human Experts?

model-releasesarxiv-cs-ai

arXiv:2603.07980v2 Announce Type: replace-cross Abstract: As language models (LMs) evolve from chat assistants to long-horizon agents capable of multi-step reasoning and tool use, existing benchmarks

ReTeach: Building a Self-Teacher through Multi-Round Reflection and Retry

arXiv:2610.11529v1 Announce Type: new Abstract: Self-distillation can improve reasoning without a separately trained, more capable teacher, but its effectiveness depends on how the self-teacher gains

safetyarxiv-cs-ai

SAVU-BENCH: A Real-World Benchmark for Spatial Audio-Visual Understanding

model-releasesarxiv-cs-ai

arXiv:2610.10624v1 Announce Type: cross Abstract: Spatial audio-visual understanding requires models to recognize not only what is present, but also where events occur and how they relate across modal