Search: “reasoning”

Detecting Data Contamination in Large Language Models

arXiv:2604.19561v1 Announce Type: new Abstract: Large Language Models (LLMs) utilize large amounts of data for their training, some of which may come from copyrighted sources. Membership Inference Att

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DT2IT-MRM: Debiased Preference Construction and Iterative Training for Multimodal Reward Modeling

DGX agent

arXiv:2604.19544v1 Announce Type: new Abstract: Multimodal reward models (MRMs) play a crucial role in aligning Multimodal Large Language Models (MLLMs) with human preferences. Training a good MRM req

safetyarxiv-cs-ai

22 Apr 2026

Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning

arXiv:2604.18639v1 Announce Type: cross Abstract: Previous LLMs-based RL studies typically follow either supervised learning with high annotation costs, or unsupervised paradigms using voting or entro

Epistemic orientation in parliamentary discourse is associated with deliberative democracy

arXiv:2604.19699v1 Announce Type: new Abstract: The pursuit of truth is central to democratic deliberation and governance, yet political discourse reflects varying epistemic orientations, ranging from

Agents

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale

arXiv:2604.17406v2 Announce Type: replace Abstract: The convergence of large language models and agents is catalyzing a new era of scientific discovery: Agentic Science. While the scientific method is

agentsarxiv-cs-ai

Agents

Explicit Trait Inference for Multi-Agent Coordination

arXiv:2604.19278v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) show promise on complex tasks but remain prone to coordination failures such as goal drift, error cascades, and misa

agentsarxiv-cs-ai

GRAFT: Geometric Refinement and Fitting Transformer for Human Scene Reconstruction

arXiv:2604.19624v1 Announce Type: new Abstract: Reconstructing physically plausible 3D human-scene interactions (HSI) from a single image currently presents a trade-off: optimization based methods off

Ground-Level Near Real-Time Modeling for PM2.5 Pollution Prediction

arXiv:2604.18973v1 Announce Type: cross Abstract: Air pollution is a worldwide public health threat that can cause or exacerbate many illnesses, including respiratory disease, cardiovascular disease,

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HalluAudio: A Comprehensive Benchmark for Hallucination Detection in Large Audio-Language Models

arXiv:2604.19300v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have recently achieved strong performance across various audio-centric tasks. However, hallucination, where models

Knowledge-Guided Time-Varying Causal Inference for Arctic Sea Ice Dynamics

arXiv:2601.17647v2 Announce Type: replace-cross Abstract: Quantifying the causal relationship between sea ice thickness and sea surface height (SSH) is essential for understanding the mechanisms drivi

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Tutorials

Learning Lifted Action Models from Unsupervised Visual Traces

arXiv:2604.19043v1 Announce Type: new Abstract: Efficient construction of models capturing the preconditions and effects of actions is essential for applying AI planning in real-world domains. Extensi

tutorialsarxiv-cs-ai

Learning to Credit the Right Steps: Objective-aware Process Optimization for Visual Generation

arXiv:2604.19234v1 Announce Type: new Abstract: Reinforcement learning, particularly Group Relative Policy Optimization (GRPO), has emerged as an effective framework for post-training visual generativ

LSTM-MAS: A Long Short-Term Memory Inspired Multi-Agent System for Long-Context Understanding

arXiv:2601.11913v2 Announce Type: replace-cross Abstract: Effectively processing long contexts remains a fundamental yet unsolved challenge for large language models (LLMs). Existing single-LLM-based

Model-Agnostic Meta Learning for Class Imbalance Adaptation

arXiv:2604.18759v1 Announce Type: new Abstract: Class imbalance is a widespread challenge in NLP tasks, significantly hindering robust performance across diverse domains and applications. We introduce

MOSA: Motion-Guided Semantic Alignment for Dynamic Scene Graph Generation

arXiv:2604.19631v1 Announce Type: new Abstract: Dynamic Scene Graph Generation (DSGG) aims to structurally model objects and their dynamic interactions in video sequences for high-level semantic under

Multilingual Language Models Encode Script Over Linguistic Structure

model-releasesarxiv-cs-cl

arXiv:2604.05090v2 Announce Type: replace Abstract: Multilingual language models (LMs) organize representations for typologically and orthographically diverse languages into a shared parameter space,

Nexusformer: Nonlinear Attention Expansion for Stable and Inheritable Transformer Scaling

arXiv:2604.19147v1 Announce Type: cross Abstract: Scaling Transformers typically necessitates training larger models from scratch, as standard architectures struggle to expand without discarding learn

OLLM: Options-based Large Language Models

arXiv:2604.19087v1 Announce Type: new Abstract: We introduce Options LLM (OLLM), a simple, general method that replaces the single next-token prediction of standard LLMs with a extit{set of learned op

OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens

arXiv:2604.18827v1 Announce Type: cross Abstract: Scaling data and artificial neural networks has transformed AI, driving breakthroughs in language and vision. Whether similar principles apply to mode

Personalized Benchmarking: Evaluating LLMs by Individual Preferences

arXiv:2604.18943v1 Announce Type: new Abstract: With the rise in capabilities of large language models (LLMs) and their deployment in real-world tasks, evaluating LLM alignment with human preferences

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Tutorials

PhotoFramer: Multi-modal Image Composition Instruction

arXiv:2512.00993v2 Announce Type: replace Abstract: Composition matters during the photo-taking process, yet many casual users struggle to frame well-composed images. To provide composition guidance,

tutorialsarxiv-cs-cv

Applications

Prompt to Pwn: Automated Exploit Generation for Smart Contracts

arXiv:2508.01371v3 Announce Type: replace-cross Abstract: Smart contracts are important for digital finance, yet they are hard to patch once deployed. Prior work has mainly explored LLMs for smart con

applicationsarxiv-cs-ai

Q-Mask: Query-driven Causal Masks for Text Anchoring in OCR-Oriented Vision-Language Models

arXiv:2604.00161v2 Announce Type: replace Abstract: Optical Character Recognition (OCR) is increasingly regarded as a foundational capability for modern vision-language models (VLMs), enabling them no

QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models

arXiv:2601.00679v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have been emerging as prominent AI models for solving many natural language tasks due to their high performance (

QTMRL: An Agent for Quantitative Trading Decision-Making Based on Multi-Indicator Guided Reinforcement Learning

arXiv:2508.20467v2 Announce Type: replace-cross Abstract: In the highly volatile and uncertain global financial markets, traditional quantitative trading models relying on statistical modeling or empi

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Quantum spatial best-arm identification via quantum walks

arXiv:2509.05890v3 Announce Type: replace-cross Abstract: Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to t

Remask, Don't Replace: Token-to-Mask Refinement in Masked Diffusion Language Models

arXiv:2604.18738v1 Announce Type: new Abstract: Masked diffusion language models such as LLaDA2.1 rely on Token-to-Token (T2T) editing to correct their own generation errors: whenever a different toke

SAVOIR: Learning Social Savoir-Faire via Shapley-based Reward Attribution

arXiv:2604.18982v1 Announce Type: new Abstract: Social intelligence, the ability to navigate complex interpersonal interactions, presents a fundamental challenge for language agents. Training such age

SCURank: Ranking Multiple Candidate Summaries with Summary Content Units for Enhanced Summarization

arXiv:2604.19185v1 Announce Type: cross Abstract: Small language models (SLMs), such as BART, can achieve summarization performance comparable to large language models (LLMs) via distillation. However

SimDiff: Depth Pruning via Similarity and Difference

arXiv:2604.19520v1 Announce Type: new Abstract: Depth pruning improves the deployment efficiency of large language models (LLMs) by identifying and removing redundant layers. A widely accepted standar

StochasTok: Improving Fine-Grained Subword Understanding in LLMs

arXiv:2506.01687v3 Announce Type: replace Abstract: Subword-level understanding is integral to numerous tasks, including understanding multi-digit numbers, spelling mistakes, abbreviations, rhyming, a

Taming Actor-Observer Asymmetry in Agents via Dialectical Alignment

arXiv:2604.19548v1 Announce Type: cross Abstract: Large Language Model agents have rapidly evolved from static text generators into dynamic systems capable of executing complex autonomous workflows. T

Temporal UI State Inconsistency in Desktop GUI Agents: Formalizing and Defending Against TOCTOU Attacks on Computer-Use Agents

arXiv:2604.18860v1 Announce Type: cross Abstract: GUI agents that control desktop computers via screenshot-and-click loops introduce a new class of vulnerability: the observation-to-action gap (mean 6

The Essence of Balance for Self-Improving Agents in Vision-and-Language Navigation

arXiv:2604.19064v1 Announce Type: new Abstract: In vision-and-language navigation (VLN), self-improvement from policy-induced experience, using only standard VLN action supervision, critically depends

The PROPER Approach to Proactivity: Benchmarking and Advancing Knowledge Gap Navigation

arXiv:2601.09926v3 Announce Type: replace Abstract: Current approaches to proactive assistance move beyond the ask-and-respond paradigm by anticipating user needs. In practice, they either burden user

safetyarxiv-cs-lg

Think Before Writing: Feature-Level Multi-Objective Optimization for Generative Citation Visibility

arXiv:2604.19113v1 Announce Type: cross Abstract: Generative answer engines expose content through selective citation rather than ranked retrieval, fundamentally altering how visibility is determined.

Toward Clinically Acceptable Chest X-ray Report Generation: A Qualitative Retrospective Pilot Study of CXRMate-2

arXiv:2604.18967v1 Announce Type: new Abstract: Chest X-ray (CXR) radiology report generation (RRG) models have shown rapid progress, yet their clinical utility remains uncertain due to limited evalua

Towards a Linguistic Evaluation of Narratives: A Quantitative Stylistic Framework

arXiv:2604.19261v1 Announce Type: new Abstract: The evaluation of narrative quality remains a complex challenge, as it involves subjective factors such as plot, character development, and emotional im

TROJail: Trajectory-Level Optimization for Multi-Turn Large Language Model Jailbreaks with Process Rewards

arXiv:2512.07761v3 Announce Type: replace Abstract: Large language models have seen widespread adoption, yet they remain vulnerable to multi-turn jailbreak attacks, threatening their safe deployment.

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URoPE: Universal Relative Position Embedding across Geometric Spaces

arXiv:2604.18747v1 Announce Type: new Abstract: Relative position embedding has become a standard mechanism for encoding positional information in Transformers. However, existing formulations are typi

VISTA: Verification In Sequential Turn-based Assessment

arXiv:2510.27052v5 Announce Type: replace Abstract: Hallucination--defined here as generating statements unsupported or contradicted by available evidence or conversational context--remains a major ob

When Can We Trust Deep Neural Networks? Towards Reliable Industrial Deployment with an Interpretability Guide

arXiv:2604.19206v1 Announce Type: new Abstract: The deployment of AI systems in safety-critical domains, such as industrial defect inspection, autonomous driving, and medical diagnosis, is severely ha

Where Fake Citations Are Made: Tracing Field-Level Hallucination to Specific Neurons in LLMs

arXiv:2604.18880v1 Announce Type: cross Abstract: LLMs frequently generate fictitious yet convincing citations, often expressing high confidence even when the underlying reference is wrong. We study t

Applications

A multimodal and temporal foundation model for virtual patient representations at healthcare system scale

arXiv:2604.18570v1 Announce Type: cross Abstract: Modern medicine generates vast multimodal data across siloed systems, yet no existing model integrates the full breadth and temporal depth of the clin

applicationsarxiv-cs-cl

A Text-To-Text Alignment Algorithm for Better Evaluation of Modern Speech Recognition Systems

arXiv:2509.24478v2 Announce Type: replace Abstract: Modern neural networks have greatly improved performance across speech recognition benchmarks. However, gains are often driven by frequent words wit

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Adaptive Forensic Feature Refinement via Intrinsic Importance Perception

arXiv:2604.16879v1 Announce Type: new Abstract: With the rapid development of generative models and multimodal content editing technologies, the key challenge faced by synthetic image detection (SID)

Arch: An AI-Native Hardware Description Language for Register-Transfer Clocked Hardware Design

arXiv:2604.05983v2 Announce Type: replace-cross Abstract: We present Arch (AI-native Register-transfer Clocked Hardware), a hardware description language for micro-architecture specification and AI-as

safetyarxiv-cs-cl

ArgBench: Benchmarking LLMs on Computational Argumentation Tasks

model-releasesarxiv-cs-cl

arXiv:2604.17366v1 Announce Type: new Abstract: Argumentation skills are an essential toolkit for large language models (LLMs). These skills are crucial in various use cases, including self-reflection