Search: “reasoning”

ReflectMT: Internalizing Reflection for Efficient and High-Quality Machine Translation

arXiv:2604.19144v1 Announce Type: new Abstract: Recent years have witnessed growing interest in applying Large Reasoning Models (LRMs) to Machine Translation (MT). Existing approaches predominantly ad

22 Apr 2026

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SpanVLA: Efficient Action Bridging and Learning from Negative-Recovery Samples for Vision-Language-Action Model

DGX agent

arXiv:2604.19710v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models offer a promising autonomous driving paradigm for leveraging world knowledge and reasoning capabilities, especially

safetyarxiv-cs-cv

22 Apr 2026

Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering

arXiv:2604.17255v1 Announce Type: new Abstract: Accurate comprehension and controllable generation of emotion and rhetoric are pivotal for enhancing the reasoning capabilities of large language models

researcharxiv-cs-cl

How Robustly do LLMs Understand Execution Semantics?

model-releasesarxiv-cs-lg

arXiv:2604.16320v1 Announce Type: cross Abstract: LLMs demonstrate remarkable reasoning capabilities, yet whether they utilize internal world models or rely on sophisticated pattern matching remains o

Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards

arXiv:2604.17957v1 Announce Type: new Abstract: Process Reward Models (PRMs) have emerged as a powerful tool for providing step-level feedback when evaluating the reasoning of Large Language Models (L

researcharxiv-cs-cl

S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2604.18512v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated remarkable progress in single-image understanding, yet effective reasoning across multiple images remain

TSVer: A Benchmark for Fact Verification Against Time-Series Evidence

arXiv:2511.01101v2 Announce Type: replace Abstract: Reasoning over temporal and numerical data, such as time series, is a crucial aspect of fact-checking. While many systems have recently been develop

What If Consensus Lies? Selective-Complementary Reinforcement Learning at Test Time

arXiv:2603.19880v2 Announce Type: replace Abstract: Test-Time Reinforcement Learning (TTRL) enables Large Language Models (LLMs) to enhance reasoning capabilities on unlabeled test streams by deriving

researcharxiv-cs-lg

KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality

arXiv:2506.19807v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs), particularly slow-thinking models, often exhibit severe hallucination, outputting incorrect content due to an in

tutorialsarxiv-cs-cl

17 Apr 2026

LongAct: Harnessing Intrinsic Activation Patterns for Long-Context Reinforcement Learning

arXiv:2604.14922v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has emerged as a critical driver for enhancing the reasoning capabilities of Large Language Models (LLMs). While recent ad

17 Apr 2026

From P(y|x) to P(y): Investigating Reinforcement Learning in Pre-train Space

arXiv:2604.14142v1 Announce Type: cross Abstract: While reinforcement learning with verifiable rewards (RLVR) significantly enhances LLM reasoning by optimizing the conditional distribution P(y|x), it

safetyarxiv-cs-cl

16 Apr 2026

RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization

arXiv:2508.00222v5 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Reward (RLVR) has significantly advanced the complex reasoning abilities of Large Language Models (LLMs

safetyarxiv-cs-cl

16 Apr 2026

Learning Chain Of Thoughts Prompts for Predicting Entities, Relations, and even Literals on Knowledge Graphs

arXiv:2604.12651v1 Announce Type: cross Abstract: Knowledge graph embedding (KGE) models perform well on link prediction but struggle with unseen entities, relations, and especially literals, limiting

15 Apr 2026

Empowering Video Translation using Multimodal Large Language Models

arXiv:2604.11283v1 Announce Type: new Abstract: Recent developments in video translation have further enhanced cross-lingual access to video content, with multimodal large language models (MLLMs) play

safetyarxiv-cs-cv

Pseudo-Unification: Entropy Probing Reveals Divergent Information Patterns in Unified Multimodal Models

arXiv:2604.10949v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) were designed to combine the reasoning ability of large language models (LLMs) with the generation capability of visi

Agents

Text-Guided 6D Object Pose Rearrangement via Closed-Loop VLM Agents

arXiv:2604.09781v1 Announce Type: new Abstract: Vision-Language Models (VLMs) exhibit strong visual reasoning capabilities, yet they still struggle with 3D understanding. In particular, VLMs often fai

agentsarxiv-cs-cv

Tracing the Thought of a Grandmaster-level Chess-Playing Transformer

arXiv:2604.10158v1 Announce Type: new Abstract: While modern transformer neural networks achieve grandmaster-level performance in chess and other reasoning tasks, their internal computation process re

safetyarxiv-cs-lg

What Factors Affect LLMs and RLLMs in Financial Question Answering?

arXiv:2507.08339v4 Announce Type: replace Abstract: Recently, large language models (LLMs) and reasoning large language models (RLLMs) have gained considerable attention from many researchers. RLLMs e

safetyarxiv-cs-cl

EgoTL: Egocentric Think-Aloud Chains for Long-Horizon Tasks

model-releasesarxiv-cs-cv

arXiv:2604.09535v1 Announce Type: new Abstract: Large foundation models have made significant advances in embodied intelligence, enabling synthesis and reasoning over egocentric input for household ta

Listener-Rewarded Thinking in VLMs for Image Preferences

arXiv:2506.22832v3 Announce Type: replace-cross Abstract: Training robust and generalizable reward models for human visual preferences is essential for aligning text-to-image and text-to-video generat

Agents

Memory Intelligence Agent

arXiv:2604.04503v3 Announce Type: replace Abstract: Deep research agents (DRAs) integrate LLM reasoning with external tools. Memory systems enable DRAs to leverage historical experiences, which are es

agentsarxiv-cs-ai

The Two-Stage Decision-Sampling Hypothesis: Understanding the Emergence of Self-Reflection in RL-Trained LLMs

arXiv:2601.01580v2 Announce Type: replace-cross Abstract: Self-reflection capabilities emerge in Large Language Models after RL post-training, with multi-turn RL achieving substantial gains over SFT c

How SAP Concur automates expense reporting with agentic AI

model-releasesgoogle-cloud-ai

For decades, expense automation relied on a simple premise: If the machine can read the text, it can do the work. But anyone who has ever tried to scan a crumpled, smudged, or sun-bleached receipt fro

10 Apr 2026

Limits of Difficulty Scaling: Hard Samples Yield Diminishing Returns in GRPO-Tuned SLMs

arXiv:2604.06298v1 Announce Type: new Abstract: Recent alignment work on Large Language Models (LLMs) suggests preference optimization can improve reasoning by shifting probability mass toward better

safetyarxiv-cs-lg

10 Apr 2026

MARCH: Evaluating the Intersection of Ambiguity Interpretation and Multi-hop Inference

arXiv:2509.22750v3 Announce Type: replace Abstract: Real-world multi-hop QA is naturally linked with ambiguity, where a single query can trigger multiple reasoning paths that require independent resol

10 Apr 2026

Where, How, and When: Query-Guided Grounding for Video Understanding

arXiv:2610.21422v1 Announce Type: cross Abstract: Understanding video content requires reasoning at multiple levels of granularity, from identifying objects to interpreting their interactions and loca

16 Oct 2026

Agents

Beyond Reward Engineering: A Data Recipe for Long-Context Reinforcement Learning

arXiv:2606.18831v2 Announce Type: replace-cross Abstract: Long-context reasoning is an essential capability for large language models, particularly when they are deployed as autonomous agents that mus

agentsarxiv-cs-ai

Bringing the borderless Lakehouse into the agentic era with innovations for Gemini

model-releasesgoogle-cloud-ai

As enterprises shift their AI usage from experimental chatbots to autonomous agents, teams are hitting a critical bottleneck: accessing and reasoning over data scattered across multiple clouds, SaaS p

Decoupled Marginal Sharpening for Training-Free Inference-Time Scaling

arXiv:2610.20483v1 Announce Type: new Abstract: We study how to improve LLM reasoning at inference time without updating model weights or using external reward models. Recent reward-free power-samplin

tutorialsarxiv-cs-lg

Double-Rollout Reinforcement Learning with Sampling-based Reward Estimation

arXiv:2610.16593v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) implemented with Group Relative Policy Optimization (GRPO) has driven substantial progress in trai

ForkGRPO: Efficient Exploration and Fine-Grained Credit Assignment for Diffusion Language Models

arXiv:2610.19408v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have advanced rapidly, yet strengthening their reasoning through reinforcement learning (RL) remains an open cha

tutorialsarxiv-cs-cl

Growing and Transferring Pathways for LLM Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2610.16489v1 Announce Type: new Abstract: Reinforcement learning (RL) can substantially improve the reasoning capabilities of large language models, but an effective training run requires consid

14 Oct 2026

One-Layer Transformers Provably Learn In-Context K-Nearest Neighbor Prediction with Chain-of-Thought

arXiv:2610.16798v1 Announce Type: new Abstract: Chain-of-Thought (CoT) enables transformers to solve complex reasoning tasks by generating intermediate reasoning steps. Despite strong empirical succes

tutorialsarxiv-cs-lg

14 Oct 2026

Thinking with Images without Coordinates

arXiv:2610.14265v1 Announce Type: new Abstract: Recent advances in multi-modal large language models have shifted toward the 'thinking with images' paradigm to improve reasoning faithfulness, yet exis

researcharxiv-cs-cv

14 Oct 2026

OccludeBench: Can VLMs Find What's Missing?

arXiv:2610.13790v1 Announce Type: cross Abstract: How well can vision-language models (VLMs) reason about what is missing from an image? We study this question with OccludeBench, a manually curated be

12 Oct 2026

U-Space: Uncovering When and Why Uncertainty Arises in Language Models [R][D]

model-releasesr-machinelearning

If you build on open-weight reasoning models, you have probably wanted a 'how sure is the model about this answer?' signal that does not cost 5x sampling, a judge model, or a labeled dataset. Hence, w

12 Oct 2026

Grounding What Shapes the Plan: Rethinking Groundedness for Physical Intelligence in Autonomous Driving

arXiv:2610.07521v1 Announce Type: new Abstract: Driving models increasingly ground reasoning in causal relations, spatial structure, perceptual evidence, and predicted futures. These advances make rea

7 Oct 2026

Learning to Simulate Individuals from Macro Social Signals

arXiv:2610.07062v1 Announce Type: cross Abstract: Large language models are increasingly used to simulate how individuals respond to new situations, yet the behavioral reasoning behind these responses

7 Oct 2026

Long-MDR: Long-Context Reinforcement Learning for Multimodal Deep-Research Agents

arXiv:2610.05195v1 Announce Type: new Abstract: The next generation of multimodal research agents must reason over long-lived research histories rather than short model completions. During a single ta

safetyarxiv-cs-cv

6 Oct 2026

I re-ran an experiment @colin_fraser ran against GPT-4o a while back to see how good it was at adding long numbers, only this time I tried Q…

model-releasessimon-willison--x

I re-ran an experiment @colin_fraser ran against GPT-4o a while back to see how good it was at adding long numbers, only this time I tried Qwen 3.8 27B running locally in both reasoning and non-reason

5 Oct 2026

Does Scaling Reinforcement Learning Really Require More Training?

arXiv:2610.01133v1 Announce Type: cross Abstract: Scaling reasoning typically spends more compute on reinforcement learning (RL) or on inference. We show that a completed RL training history can yield

2 Oct 2026

Scaling Clinical Judgment to Evaluate Medical AI

arXiv:2609.12822v2 Announce Type: replace Abstract: Blinded physician evaluation has been considered by many to be the gold standard for assessing clinical reasoning in large language models (LLMs). T

2 Oct 2026

Task-Adaptive Grounded 3D-Programmers Using 2D VLMs

arXiv:2610.02021v1 Announce Type: cross Abstract: Recent vision-language models (VLMs) exhibit remarkable generalization and reasoning abilities, yet 3D understanding in these models is limited by dat

2 Oct 2026

GraphMAS: A Systematic Benchmark of Multi-Agent Coordination for Graph Learning

model-releasesarxiv-cs-lg

arXiv:2609.39777v1 Announce Type: new Abstract: LLM-based multi-agent systems coordinate specialized reasoning through aggregation, interaction, and adaptive control, yet their potential for graph lea

1 Oct 2026

Making LLMs Say What They Think: Measuring and Improving CoT-Interpretability Alignment

arXiv:2609.38972v1 Announce Type: cross Abstract: Chain-of-thought (CoT) traces often serve as a proxy for how Large Language Models (LLMs) arrive at their answers. However, growing evidence shows tha

1 Oct 2026

Local Ai

On-Policy Visual Evidence Distillation

arXiv:2609.36838v1 Announce Type: cross Abstract: Visual agents solve problems by interleaving reasoning with image operations, and on-policy distillation (OPD) provides guidance from a strong teacher

local-aiarxiv-cs-ai

30 Sept 2026

Beyond Bag-of-Words: Diagnosing Compositional Binding Failures in Vision-Language Models

arXiv:2602.02043v2 Announce Type: replace-cross Abstract: Modern vision-language models struggle with basic compositional reasoning, failing to bind attributes to objects or relations to their referen

28 Sept 2026

A new, no-compromises database architecture for the agentic era