Search: “reasoning”

ChemPro: A Progressive Chemistry Benchmark for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2602.03108v3 Announce Type: replace Abstract: We introduce ChemPro, a progressive benchmark with 4100 natural language question-answer pairs in Chemistry, across 4 coherent sections of difficult

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Applications

CLASP: Closed-loop Asynchronous Spatial Perception for Open-vocabulary Desktop Object Grasping

DGX agent

arXiv:2604.11320v1 Announce Type: new Abstract: Robot grasping of desktop object is widely used in intelligent manufacturing, logistics, and agriculture.Although vision-language models (VLMs) show str

applicationsarxiv-cs-ro

14 Apr 2026

Hardware

CodeQuant: Unified Clustering and Quantization for Enhanced Outlier Smoothing in Low-Precision Mixture-of-Experts

arXiv:2604.10496v1 Announce Type: new Abstract: Outliers have emerged as a fundamental bottleneck in preserving accuracy for low-precision large models, particularly within Mixture-of-Experts (MoE) ar

hardwarearxiv-cs-lg

Context Matters: Vision-Based Depression Detection Comparing Classical and Deep Approaches

arXiv:2604.10344v1 Announce Type: new Abstract: The classical approach to detecting depression from vision emphasizes interpretable features, such as facial expression, and classifiers such as the Sup

safetyarxiv-cs-cv

CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models

arXiv:2604.10031v1 Announce Type: cross Abstract: Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demon

Credit-Budgeted ICPC-Style Coding: When Agents Must Pay for Every Decision

arXiv:2604.10182v1 Announce Type: new Abstract: Current evaluations of autonomous coding agents assume an unrealistic, infinite-resource environment. However, real-world software engineering is a reso

DarwinNet: An Evolutionary Network Architecture for Agent-Driven Protocol Synthesis

arXiv:2604.01236v2 Announce Type: replace-cross Abstract: Traditional network architectures suffer from severe protocol ossification and structural fragility due to their reliance on static, human-def

DecAlign: Hierarchical Cross-Modal Alignment for Decoupled Multimodal Representation Learning

arXiv:2503.11892v3 Announce Type: replace Abstract: Multimodal representation learning aims to capture both shared and complementary semantic information across multiple modalities. However, the intri

safetyarxiv-cs-cv

Decoding Ancient Oracle Bone Script via Generative Dictionary Retrieval

arXiv:2604.09668v1 Announce Type: cross Abstract: Understanding humanity's earliest writing systems is crucial for reconstructing civilization's origins, yet many ancient scripts remain undeciphered.

Detecting RAG Extraction Attack via Dual-Path Runtime Integrity Game

arXiv:2604.10717v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems augment large language models with external knowledge, yet introduce a critical security vulnerability: R

Dialectic-Med: Mitigating Diagnostic Hallucinations via Counterfactual Adversarial Multi-Agent Debate

arXiv:2604.11258v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) in healthcare suffer from severe confirmation bias, often hallucinating visual details to support initial, pote

safetyarxiv-cs-cl

DiffClean: Diffusion-based Makeup Removal for Accurate Age Estimation

arXiv:2507.13292v3 Announce Type: replace Abstract: Accurate age verification can protect underage users from unauthorized access to online platforms and e-commerce sites that provide age-restricted s

applicationsarxiv-cs-cv

Do BERT Embeddings Encode Narrative Dimensions? A Token-Level Probing Analysis of Time, Space, Causality, and Character in Fiction

arXiv:2604.10786v1 Announce Type: cross Abstract: Narrative understanding requires multidimensional semantic structures. This study investigates whether BERT embeddings encode dimensions of fictional

Dual-Margin Embedding for Fine-Grained Long-Tailed Plant Taxonomy

arXiv:2512.18994v2 Announce Type: replace Abstract: Taxonomic classification of ecological families, genera, and species underpins biodiversity monitoring and conservation. Existing computer vision me

applicationsarxiv-cs-cv

Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models

arXiv:2604.10567v1 Announce Type: cross Abstract: Diffusion-based language models (dLLMs) have emerged as a promising alternative to autoregressive language models, offering the potential for parallel

Efficient Emotion-Aware Iconic Gesture Prediction for Robot Co-Speech

arXiv:2604.11417v1 Announce Type: cross Abstract: Co-speech gestures increase engagement and improve speech understanding. Most data-driven robot systems generate rhythmic beat-like motion, yet few in

End-to-end Contrastive Language-Speech Pretraining Model For Long-form Spoken Question Answering

arXiv:2511.09282v3 Announce Type: replace-cross Abstract: Significant progress has been made in spoken question answering (SQA) in recent years. However, many existing methods, including large audio l

safetyarxiv-cs-cl

Local Ai

Enhancing Geo-localization for Crowdsourced Flood Imagery via LLM-Guided Attention

arXiv:2512.11811v3 Announce Type: replace-cross Abstract: Crowdsourced social media imagery provides real-time visual evidence of urban flooding but often lacks reliable geographic metadata for emerge

local-aiarxiv-cs-ai

Escaping the Context Bottleneck: Active Context Curation for LLM Agents via Reinforcement Learning

model-releasesarxiv-cs-ai

arXiv:2604.11462v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle with long-horizon tasks due to the 'context bottleneck' and the 'lost-in-the-middle' phenomenon, where accumulated

Evaluating Cooperation in LLM Social Groups through Elected Leadership

arXiv:2604.11721v1 Announce Type: cross Abstract: Governing common-pool resources requires agents to develop enduring strategies through cooperation and self-governance to avoid collective failure. Wh

EvoESAP: Non-Uniform Expert Pruning for Sparse MoE

arXiv:2603.06003v2 Announce Type: replace Abstract: Sparse Mixture-of-Experts (SMoE) language models achieve strong capability at low per-token compute, yet deployment remains constrained by memory fo

researcharxiv-cs-lg

Exploring Knowledge Purification in Multi-Teacher Knowledge Distillation for LLMs

arXiv:2602.01064v2 Announce Type: replace Abstract: Knowledge distillation has emerged as a pivotal technique for transferring knowledge from stronger large language models (LLMs) to smaller, more eff

researcharxiv-cs-cl

Factorizing formal contexts from closures of necessity operators

arXiv:2604.09582v1 Announce Type: new Abstract: Factorizing datasets is an interesting process in a multitude of approaches, but many times it is not possible or efficient the computation of a factori

FF3R: Feedforward Feature 3D Reconstruction from Unconstrained views

arXiv:2604.09862v1 Announce Type: new Abstract: Recent advances in vision foundation models have revolutionized geometry reconstruction and semantic understanding. Yet, most of the existing approaches

FGML-DG: Feynman-Inspired Cognitive Science Paradigm for Cross-Domain Medical Image Segmentation

arXiv:2604.10524v1 Announce Type: new Abstract: In medical image segmentation across multiple modalities (e.g., MRI, CT, etc.) and heterogeneous data sources (e.g., different hospitals and devices), D

safetyarxiv-cs-cv

FlashMem: Distilling Intrinsic Latent Memory via Computation Reuse

model-releasesarxiv-cs-cl

arXiv:2601.05505v2 Announce Type: replace Abstract: The stateless architecture of Large Language Models inherently lacks the mechanism to preserve dynamic context, compelling agents to redundantly rep

From Pixels to Digital Agents: An Empirical Study on the Taxonomy and Technological Trends of Reinforcement Learning Environments

arXiv:2603.23964v2 Announce Type: replace Abstract: The remarkable progress of reinforcement learning (RL) is intrinsically tied to the environments used to train and evaluate artificial agents. Movin

Frugal Knowledge Graph Construction with Local LLMs: A Zero-Shot Pipeline, Self-Consistency and Wisdom of Artificial Crowds

model-releasesarxiv-cs-ai

arXiv:2604.11104v1 Announce Type: new Abstract: This paper presents an empirical study of a multi-model zero-shot pipeline for knowledge graph construction and exploitation, executed entirely through

GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents

arXiv:2603.24329v2 Announce Type: replace-cross Abstract: Multimodal LLMs are increasingly deployed as perceptual backbones for autonomous agents in 3D environments, from robotics to virtual worlds. T

Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models

arXiv:2604.10748v1 Announce Type: cross Abstract: Generating multiple-choice questions (MCQs) with difficulty estimation remains challenging in automated MCQ-generation systems used in adaptive, AI-as

applicationsarxiv-cs-ai

Graph-RHO: Critical-path-aware Heterogeneous Graph Network for Long-Horizon Flexible Job-Shop Scheduling

arXiv:2604.10073v1 Announce Type: cross Abstract: Long-horizon Flexible Job-Shop Scheduling~(FJSP) presents a formidable combinatorial challenge due to complex, interdependent decisions spanning exten

Tutorials

HO-Flow: Generalizable Hand-Object Interaction Generation with Latent Flow Matching

arXiv:2604.10836v1 Announce Type: new Abstract: Generating realistic 3D hand-object interactions (HOI) is a fundamental challenge in computer vision and robotics, requiring both temporal coherence and

tutorialsarxiv-cs-cv

Tutorials

How to Design a Compact High-Throughput Video Camera?

arXiv:2604.10619v1 Announce Type: new Abstract: High throughput video acquisition is a challenging problem and has been drawing increasing attention. Existing high throughput imaging systems splice hu

tutorialsarxiv-cs-cv

🚨 In 2 weeks, a final decision on amendments to the EU AI Act and the GDPR will be made. What is at stake is nothing other than the future …

🚨 In 2 weeks, a final decision on amendments to the EU AI Act and the GDPR will be made. What is at stake is nothing other than the future of Europe. Many don't know, but the stream of events leading

safetyyann-lecun--x

Inferring World Belief States in Dynamic Real-World Environments

arXiv:2604.11020v1 Announce Type: new Abstract: We investigate estimating a human's world belief state using a robot's observations in a dynamic, 3D, and partially observable environment. The methods

applicationsarxiv-cs-ro

Investigating Vaccine Buyer's Remorse: Post-Vaccination Decision Regret in COVID-19 Social Media Using Politically Diverse Human Annotation

model-releasesarxiv-cs-lg

arXiv:2604.09626v1 Announce Type: cross Abstract: A significant gap exists in datasets regarding post-COVID-19 vaccination experiences, particularly ``vaccine buyer's remorse''. Understanding the prev

ITIScore: An Image-to-Text-to-Image Rating Framework for the Image Captioning Ability of MLLMs

model-releasesarxiv-cs-cv

arXiv:2604.03765v2 Announce Type: replace Abstract: Recent advances in multimodal large language models (MLLMs) have greatly improved image understanding and captioning capabilities. However, existing

It’s not governance slowing down enterprise AI — it’s the lack of it, says Qlik executive

Enterprises are chasing AI models at a dizzying pace, yet the organizations pulling ahead are the ones that paused to build something less glamorous: a trusted, governed data foundation. Pressure is m

agentssiliconangle

KiseKloset for Fashion Retrieval and Recommendation

arXiv:2506.23471v2 Announce Type: replace-cross Abstract: The global fashion e-commerce industry has become integral to people's daily lives, leveraging technological advancements to offer personalize

Latent Structure of Affective Representations in Large Language Models

arXiv:2604.07382v2 Announce Type: replace-cross Abstract: The geometric structure of latent representations in large language models (LLMs) is an active area of research, driven in part by its implica

Lectures on AI for Mathematics

arXiv:2604.11504v1 Announce Type: new Abstract: This book provides a comprehensive and accessible introduction to the emerging field of AI for mathematics. It covers the core principles and diverse ap

LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation

arXiv:2604.11789v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have achieved remarkable progress in general-purpose vision--language understanding, yet they remain limited in tasks req

MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward Optimization

arXiv:2601.07208v2 Announce Type: replace-cross Abstract: Group-Relative Policy Optimization (GRPO) has emerged as an efficient paradigm for aligning Large Language Models (LLMs), yet its efficacy is

safetyarxiv-cs-cl

Local Ai

MAFIG: Multi-agent Driven Formal Instruction Generation Framework

arXiv:2604.10989v1 Announce Type: new Abstract: Emergency situations in scheduling systems often trigger local functional failures that undermine system stability and even cause system collapse. Exist

local-aiarxiv-cs-ai

MASH: Modeling Abstention via Selective Help-Seeking

arXiv:2510.01152v2 Announce Type: replace Abstract: LLMs cannot reliably recognize their parametric knowledge boundaries and often hallucinate answers to outside-of-boundary questions. In this paper,

agentsarxiv-cs-cl

Measuring What Matters!! Assessing Therapeutic Principles in Mental-Health Conversation

model-releasesarxiv-cs-cl

arXiv:2604.05795v2 Announce Type: replace Abstract: The increasing use of large language models in mental health applications calls for principled evaluation frameworks that assess alignment with psyc

METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues

arXiv:2604.11427v1 Announce Type: cross Abstract: Developing non-collaborative dialogue agents traditionally requires the manual, unscalable codification of expert strategies. We propose ours, a metho

MGA: Memory-Driven GUI Agent for Observation-Centric Interaction

arXiv:2510.24168v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have significantly advanced GUI agents, yet long-horizon automation remains constrained by two critical bot