Search: “reasoning”

SEPAL: Separated Expert Pairs with Answer-Level Fusion for Reliable LLM Collaboration

arXiv:2609.39645v1 Announce Type: cross Abstract: Multi-agent collaboration lets large language models (LLMs) improve question answering through deliberation and feedback. Yet shared discussion couple

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Shared Weights, Selected Computations: How Looped Transformers Route What Each Loop Does

DGX agent

arXiv:2609.39892v1 Announce Type: new Abstract: Looped Transformers repeatedly apply the same set of Transformer layers, giving them a recurrent architecture for latent computation. Their strong perfo

safetyarxiv-cs-lg

1 Oct 2026

SimEX: Simulation-Integrated Robotics AutoResearch

arXiv:2609.38982v1 Announce Type: cross Abstract: Coding agents powered by large language models (LLMs) have shown remarkable abilities to autonomously reason about and achieve goals in the digital wo

StreamDecisionBench: Evaluating Decisions in Force on Evolving Language Streams

arXiv:2609.38612v1 Announce Type: new Abstract: As natural language drives more applications, language models increasingly run inside programs as decision components: the program sends them the curren

researcharxiv-cs-cl

Local Ai

TACTIC: Temporal and Context-Aware LLM Tactical Planning for Roadside LiDAR Attacks

arXiv:2609.39969v1 Announce Type: cross Abstract: Physical LiDAR attacks are often evaluated using fixed primitives and manually selected parameters, despite their strong dependence on surrounding tra

local-aiarxiv-cs-ai

Thinking Outside the Box: Can Language Models Rely on External Guidance Selectively?

arXiv:2609.39578v1 Announce Type: new Abstract: Agent harnesses often improve language models with human-designed workflows, but as models grow more capable, unreliable guidance can increasingly const

agentsarxiv-cs-cl

Towards Better Exploration in Sequential Test-Time Scaling

arXiv:2609.39632v1 Announce Type: new Abstract: Test-time scaling improves language model reasoning by spending additional compute at inference. However, both classes of existing methods often fail to

researcharxiv-cs-lg

Unlearning Deceptive Behaviors in LLMs with Contrastive Forget Sets

arXiv:2609.38909v1 Announce Type: cross Abstract: Large language models often know the truth and say otherwise: a model that answers correctly when asked neutrally will affirm a user's mistaken belief

researcharxiv-cs-ai

What's the best setup for Qwen3.8 27b for a 16 gig VRAM?

model-releasesr-localllama

Hello guys! I have been experimenting with qwen 3.8 for a long time and I hadn't been able to get reasonable speed. I am on a 5060Ti 16 GB, and although this gpu can game, I am aware that AI demands m

Where MLLMs Fail and Why: Causal Task Decomposition for Capability Failure Diagnosis

arXiv:2609.38851v1 Announce Type: cross Abstract: End-to-end accuracy on compositional tasks records how often MLLMs fail, but cannot distinguish whether a failure reflects an intrinsic deficit in the

AdaptArena: Evaluating Test-Time Personalization of Web Agents

arXiv:2609.36488v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong performance on complex web navigation tasks, yet they remain brittle in real-world settings w

Adaptive Consistency Graph for Long-Horizon Agents

arXiv:2609.32754v2 Announce Type: replace Abstract: Large language model agents can often make reasonable local decisions on short tasks, yet their performance degrades when success requires long sequ

Backdoor in the Loop: Compromising Agentic Search via Malicious Retrievers

arXiv:2609.37468v1 Announce Type: cross Abstract: Agentic retrieval-augmented generation (RAG) interleaves reasoning with repeated retrieval, giving the retriever influence over both the evidence an a

Beyond Symmetric Agents: Cognitive Diversity and Multi-Agent Debate in Small Language Models

arXiv:2609.35875v1 Announce Type: new Abstract: Multi-agent debate (MAD) reportedly improves reasoning and factuality over single-model inference, but prior work treats agents as symmetric peers, leav

Block Sparse Flash Attention

arXiv:2512.07011v2 Announce Type: replace-cross Abstract: Modern large language models increasingly require long contexts for reasoning and multi-document tasks, but attention's quadratic complexity c

CADOC: Cache-Aware Dynamic Object Context for Long-Horizon Agents

arXiv:2609.37012v1 Announce Type: new Abstract: For a long-horizon agent, context is the bottleneck: the history is resent with every request, the window caps task length, and reasoning degrades as th

Can Language Models Learn to Forecast Stock Prices

arXiv:2609.36914v1 Announce Type: new Abstract: Post-training has been shown to significantly improve language models' performance on tasks with verifiable outcomes, including mathematical reasoning,

CorrGRPO: Correlation-Normalized GRPO for Multi-Reward Learning

arXiv:2609.36820v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) is widely used to train reasoning language models, where it computes advantages by centering and normalizing

safetyarxiv-cs-cl

Applications

Devils in Question Relay: Source-Conditioned Relay Steering to Mitigate Hallucinations in Audio-visual Large Language Models

arXiv:2609.37568v1 Announce Type: new Abstract: Audio-visual large language models (AVLLMs) have made remarkable progress in multimodal understanding and reasoning through interactions among visual, a

applicationsarxiv-cs-cl

Distilled Reinforcement Learning for LLM Post-training

arXiv:2607.17247v2 Announce Type: replace-cross Abstract: Large language model (LLM) post-training is essential for improving reasoning, adaptation, and alignment. Existing methods mainly follow two p

Divide and Inject: Can Agents Reconstruct an Indirect Prompt Injection from Fragments?

arXiv:2609.36576v1 Announce Type: new Abstract: Agentic systems are now being widely used to orchestrate tools and reason over long contexts. However, the improving capabilities of the large language

doPlan: A Variable-Horizon Dataset for Multi-Stage Language-Conditioned Planning in Autonomous Driving

arXiv:2609.38028v1 Announce Type: cross Abstract: Autonomous vehicles interacting with passengers through natural language must reason beyond immediate commands. Passenger intent may span multiple sta

HiTS-CL: A Continual Learning Framework for Long-Horizon Temporal Knowledge Graph Extrapolation

arXiv:2609.36559v1 Announce Type: cross Abstract: Extrapolative temporal knowledge graph reasoning (TKGR) predicts future facts from historical snapshots. Most existing methods train once on an early

How Medical VLMs Underutilize Their Vision Encoders: A Dermatology Perspective

arXiv:2609.36557v1 Announce Type: cross Abstract: Medical Vision-Language Models (VLMs) show significant promise for clinical image understanding, offering accurate diagnosis with interpretable reason

researcharxiv-cs-ai

Inducing Process Supervision from Outcome-Only Reinforcement Learning

arXiv:2609.36641v1 Announce Type: cross Abstract: Process reward models (PRMs) have become a key component for LLMs, as their step-level feedback supports both post-training and test-time reasoning. H

KUPAS MASTER: Distilling the Tacit Expertise of Master Practitioners into Agent-Ready Experience Corpora

arXiv:2609.37673v1 Announce Type: new Abstract: Experienced professionals know more than just facts and conclusions. They know which cues matter, why a judgment is reasonable, and which action to take

Larry Caused the Car to Stop, But the Model Didn't Notice: Transformer Blindness to the M-Heuristic

arXiv:2609.37497v1 Announce Type: new Abstract: Modern transformer models excel at capturing semantic relationships through sentence embeddings, yet their ability to perform pragmatic reasoning remain

Learning Meta-Skills for Agent Harness Design in Test-Time AI4AI

arXiv:2609.38143v1 Announce Type: new Abstract: Agent performance depends on both reasoning ability and the environment in which it acts. We study test-time AI-for-AI, asking how a Builder can learn t

Applications

Long-Term Memory-Guided Enhancement for Target Perception in Audio-Language Models

arXiv:2609.36577v1 Announce Type: cross Abstract: Audio large language models (ALLMs) can reason about the content of audio recordings to perform complex tasks. However, these capabilities usually col

applicationsarxiv-cs-ai

Looped Transformers as Optimizers

arXiv:2609.37379v1 Announce Type: new Abstract: Looped Transformers provide a parameter-efficient approach to depth scaling by repeatedly applying shared Transformer blocks. Recent reasoning models ha

MotorMind: Scaffolding General Vision Language Models for Zero-Shot Robot Manipulation

arXiv:2609.38078v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced robotic manipulation, but their zero-shot generalization in new tasks and environments remains limited

safetyarxiv-cs-ro

Local Ai

ollama multi gpu installer bugs

I've been struggling with the ollama update process. I have both nvidia and amd GPUs in my system. I have two instances of ollama running on different ports for this to work around issues. AMD 7800xt

local-air-ollama

OmniRoute: Mapping Temporal Semantic Evidence to Audio-Visual Token Budgets for Efficient Omnimodal Large Language Models

arXiv:2609.37052v1 Announce Type: new Abstract: Omnimodal large language models (Omni-LLMs) encode audio and visual streams into temporally interleaved token sequences for multimodal reasoning. Howeve

Pi + llama-server randomly hung

model-releasesr-localllama

I can't seem to find what's wrong. I'm using Pi for my llama-server and sometimes it just stops processing for some reason and stuck after tool call. Logs seems to think that it's finished its job whi

Principled Thoughts for Latent Recursive LLM Systems

arXiv:2609.36159v1 Announce Type: new Abstract: Large language models can reason in continuous space instead of decoded text, by recurring on their own hidden states or by passing those states between

RoboHarn-Evo: Evolving Hierarchical Physical Knowledge for Self-Improving Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.37583v1 Announce Type: new Abstract: Vision-language models can coordinate long-horizon robot manipulation, yet successful task reasoning still depends on whether local physical interaction

Seek Before You Move: Evidence Seeking for Progress Grounding in Vision-Language Navigation

arXiv:2609.37353v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) requires agents to continuously ground task progress from long-horizon instructions and partial egocentric observations

Local Ai

Task-Oriented Visual Feature Compression via Residual Vector Quantization for Device-Edge Multimodal Inference

arXiv:2609.37090v1 Announce Type: new Abstract: Large multimodal models (LMMs) support diverse visual understanding and reasoning tasks but are often impractical to run entirely on resource-constraine

local-aiarxiv-cs-cv

Trajectory Soup: Pushing the Compute-Scaling Frontier of LLM Mid-training via Diverse Trajectories

arXiv:2609.37169v1 Announce Type: cross Abstract: Mid-training equips pretrained large language models with specialized and reasoning capabilities, but the returns of this stage are bounded since addi

TReVS: Integrating Textual Relevance and Visual Saliency for Efficient Vision-Language Model Token Pruning

arXiv:2609.37581v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel at visual understanding and reasoning but often incur substantial inference costs due to the large number of visua

researcharxiv-cs-ai

Unlocking the Critic: Reward-Free Policy Optimization for LLM Post-Training

arXiv:2609.37119v1 Announce Type: cross Abstract: Recent approaches to reinforcement learning (RL) post-training for large language models increasingly remove the critic to reduce training instability

What Makes Recurrence Effective in Looped Language Models?

arXiv:2609.36636v1 Announce Type: cross Abstract: Looped language models (LoopLMs) increase computational depth through parameter sharing, offering a path to scale inference computation without adding

When to Retrieve, When to Stay: Uncertainty-Aware Temporal Evidence Allocation for Streaming Video-LLMs

arXiv:2609.37345v1 Announce Type: new Abstract: Streaming video understanding requires Video Large Language Models (Video-LLMs) to reason over continuous visual streams under causal constraints. As th

A Surgical Foundation Model Reveals Task-Dependent Label Efficiency

arXiv:2609.31821v1 Announce Type: new Abstract: Developing label-efficient models is a central challenge in surgical AI due to the high cost and scarcity of expert annotation. While self-supervised fo

AD-E2E-JEPA: A Joint-Embedding Predictive Architecture For End-to-End Autonomous Driving

arXiv:2609.34085v1 Announce Type: cross Abstract: Autonomous driving requires extit{world models} that can understand the physical world, reason and plan, and operate safely. In this paper, we first s

Allspark: Weak to Strong Transfer via Alternating Chain of Thought

arXiv:2609.32913v1 Announce Type: new Abstract: Recent progress in frontier models has renewed interest in large-scale reinforcement learning (RL), but the cost of generating large-model rollouts make

Amnesia by Design, Memory By Necessity: Persistent State for Document Intelligence

arXiv:2609.32041v1 Announce Type: new Abstract: Modern Document AI reads contracts, extracts fields, reasons over tables, and grounds answers to page regions, then forgets everything. Processing an am

Beyond Token Savings: A Systematic Study of Context Compression in LLM Agents

arXiv:2609.32961v1 Announce Type: new Abstract: As LLM agents tackle longer tasks, they increasingly compress growing histories of reasoning, actions, and tool outputs. Compression can reduce token us