Search: “llm”

Encoder-Free Human Motion Understanding via Structured Motion Descriptions

arXiv:2604.21668v1 Announce Type: new Abstract: The world knowledge and reasoning capabilities of text-based large language models (LLMs) are advancing rapidly, yet current approaches to human motion

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Engaged AI Governance: Addressing the Last Mile Challenge Through Internal Expert Collaboration

DGX agent

arXiv:2604.21554v1 Announce Type: new Abstract: Under the EU AI Act, translating AI governance requirements into software development practice remains challenging. While AI governance frameworks exist

safetyarxiv-cs-ai

24 Apr 2026

Enhancing Science Classroom Discourse Analysis through Joint Multi-Task Learning for Reasoning-Component Classification

arXiv:2604.21137v1 Announce Type: cross Abstract: Analyzing the reasoning patterns of students in science classrooms is critical for understanding knowledge construction mechanism and improving instru

Entropy Ratio Clipping as a Soft Global Constraint for Stable Reinforcement Learning

arXiv:2512.05591v2 Announce Type: replace-cross Abstract: Large language model post-training relies on reinforcement learning to improve model capability and alignment quality. However, the off-policy

Evaluating AI Meeting Summaries with a Reusable Cross-Domain Pipeline

arXiv:2604.21345v1 Announce Type: new Abstract: We present a reusable evaluation pipeline for generative AI applications, instantiated for AI meeting summaries and released with a public artifact pack

Evaluation of Automatic Speech Recognition Using Generative Large Language Models

arXiv:2604.21928v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) is traditionally evaluated using Word Error Rate (WER), a metric that is insensitive to meaning. Embedding-based sema

Focus on What Matters: Fisher-Guided Adaptive Multimodal Fusion for Vulnerability Detection

arXiv:2601.02438v3 Announce Type: replace-cross Abstract: Software vulnerability detection can be formulated as a binary classification problem that determines whether a given code snippet contains se

Forget, Then Recall: Learnable Compression and Selective Unfolding via Gist Sparse Attention

arXiv:2604.20920v1 Announce Type: new Abstract: Scaling large language models to long contexts is challenging due to the quadratic computational cost of full attention. Mitigation approaches include K

researcharxiv-cs-lg

From Tokens to Concepts: Leveraging SAE for SPLADE

arXiv:2604.21511v1 Announce Type: cross Abstract: Learned Sparse IR models, such as SPLADE, offer an excellent efficiency-effectiveness tradeoff. However, they rely on the underlying backbone vocabula

GS-Quant: Granular Semantic and Generative Structural Quantization for Knowledge Graph Completion

arXiv:2604.21649v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown immense potential in Knowledge Graph Completion (KGC), yet bridging the modality gap between continuous graph em

Han Dan Xue Bu (Mimicry) or Qing Chu Yu Lan (Mastery)? A Cognitive Perspective on Reasoning Distillation in Large Language Models

arXiv:2601.05019v2 Announce Type: replace-cross Abstract: Recent Large Reasoning Models trained via reinforcement learning exhibit a 'natural' alignment with human cognitive costs. However, we show th

HiCrew: Hierarchical Reasoning for Long-Form Video Understanding via Question-Aware Multi-Agent Collaboration

arXiv:2604.21444v1 Announce Type: new Abstract: Long-form video understanding remains fundamentally challenged by pervasive spatiotemporal redundancy and intricate narrative dependencies that span ext

InVitroVision: a Multi-Modal AI Model for Automated Description of Embryo Development using Natural Language

arXiv:2604.21061v1 Announce Type: new Abstract: The application of artificial intelligence (AI) in IVF has shown promise in improving consistency and standardization of decisions, but often relies on

Machine Behavior in Relational Moral Dilemmas: Moral Rightness, Predicted Human Behavior, and Model Decisions

arXiv:2604.21871v1 Announce Type: new Abstract: Human moral judgment is context-dependent and modulated by interpersonal relationships. As large language models (LLMs) increasingly function as decisio

Mitigating Lost in Multi-turn Conversation via Curriculum RL with Verifiable Accuracy and Abstention Rewards

arXiv:2510.18731v2 Announce Type: replace-cross Abstract: Large Language Models demonstrate strong capabilities in single-turn instruction following but suffer from Lost-in-Conversation (LiC), a degra

On the Relationship between Bayesian Networks and Probabilistic Structural Causal Models

arXiv:2603.27406v2 Announce Type: replace Abstract: In this paper, the relationship between probabilistic graphical models, in particular Bayesian networks, and causal diagrams, also called structural

PosterForest: Hierarchical Multi-Agent Collaboration for Scientific Poster Generation

arXiv:2508.21720v2 Announce Type: replace Abstract: Automating scientific poster generation requires hierarchical document understanding and coherent content-layout planning. Existing methods often re

RealRoute: Dynamic Query Routing System via Retrieve-then-Verify Paradigm

arXiv:2604.20860v1 Announce Type: cross Abstract: Despite the success of Retrieval-Augmented Generation (RAG) in grounding LLMs with external knowledge, its application over heterogeneous sources (e.g

Revisiting Content-Based Music Recommendation: Efficient Feature Aggregation from Large-Scale Music Models

arXiv:2604.20847v1 Announce Type: cross Abstract: Music Recommendation Systems (MRSs) are a cornerstone of modern streaming platforms. Existing recommendation models, spanning both recall and ranking

Revisiting Non-Verbatim Memorization in Large Language Models: The Role of Entity Surface Forms

arXiv:2604.21882v1 Announce Type: new Abstract: Understanding what kinds of factual knowledge large language models (LLMs) memorize is essential for evaluating their reliability and limitations. Entit

Schoenfeld's Anatomy of Mathematical Reasoning by Language Models

arXiv:2512.19995v2 Announce Type: replace-cross Abstract: Large language models increasingly expose reasoning traces, yet their underlying cognitive structure and steps remain difficult to identify an

Structural Quality Gaps in Practitioner AI Governance Prompts: An Empirical Study Using a Five-Principle Evaluation Framework

arXiv:2604.21090v1 Announce Type: cross Abstract: AI governance programmes increasingly rely on natural language prompts to constrain and direct AI agent behaviour. These prompts function as executabl

Sub-Token Routing in LoRA for Adaptation and Query-Aware KV Compression

arXiv:2604.21335v1 Announce Type: cross Abstract: Sub-token routing offers a finer control axis for transformer efficiency than the coarse units used in most prior work, such as tokens, pages, heads,

Task-Driven Co-Design of Heterogeneous Multi-Robot Systems

arXiv:2604.21894v1 Announce Type: new Abstract: Designing multi-agent robotic systems requires reasoning across tightly coupled decisions spanning heterogeneous domains, including robot design, fleet

agentsarxiv-cs-ro

Ternary Memristive Logic: Hardware for Reasoning Realized via Domain Algebra

arXiv:2604.20891v1 Announce Type: cross Abstract: Memristive crossbars store numerical weights needing aggregation and decoding; a single junction means nothing alone. This paper presents a fundamenta

Unlocking the Power of Large Language Models for Multi-table Entity Matching

arXiv:2604.21238v1 Announce Type: new Abstract: Multi-table entity matching (MEM) addresses the limitations of dual-table approaches by enabling simultaneous identification of equivalent entities acro

When Bigger Isn't Better: A Comprehensive Fairness Evaluation of Political Bias in Multi-News Summarisation

arXiv:2604.21309v1 Announce Type: new Abstract: Multi-document news summarisation systems are increasingly adopted for their convenience in processing vast daily news content, making fairness across d

XtraGPT: Context-Aware and Controllable Academic Paper Revision via Human-AI Collaboration

arXiv:2505.11336v4 Announce Type: replace Abstract: Despite the growing adoption of large language models (LLMs) in academic workflows, their capabilities remain limited in supporting high-quality sci

Hardware

A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing

arXiv:2604.20129v1 Announce Type: new Abstract: The Synergistic Collapse occurs when scaling beyond 100 agents causes superlinear performance degradation that individual optimizations cannot prevent.

hardwarearxiv-cs-lg

AgentSOC: A Multi-Layer Agentic AI Framework for Security Operations Automation

arXiv:2604.20134v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) increasingly encounter difficulties in correlating heterogeneous alerts, interpreting multi-stage attack progressio

Hardware

Algorithm and Hardware Co-Design for Efficient Complex-Valued Uncertainty Estimation

arXiv:2604.19993v1 Announce Type: cross Abstract: Complex-Valued Neural Networks (CVNNs) have significant advantages in handling tasks that involve complex numbers. However, existing CVNNs are unable

hardwarearxiv-cs-lg

Aligning Human-AI-Interaction Trust for Mental Health Support: Survey and Position for Multi-Stakeholders

arXiv:2604.20166v1 Announce Type: new Abstract: Building trustworthy AI systems for mental health support is a shared priority across stakeholders from multiple disciplines. However, 'trustworthy' rem

Auditing and Controlling AI Agent Actions in Spreadsheets

arXiv:2604.20070v1 Announce Type: cross Abstract: Advances in AI agent capabilities have outpaced users' ability to meaningfully oversee their execution. AI agents can perform sophisticated, multi-ste

Co-Located Tests, Better AI Code: How Test Syntax Structure Affects Foundation Model Code Generation

arXiv:2604.19826v1 Announce Type: cross Abstract: AI coding assistants increasingly generate code alongside tests. How developers structure test code, whether inline with the implementation or in sepa

CodeRL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment

arXiv:2510.18471v2 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) excel at code generation by learning from vast code corpora, a fundamental semantic gap remains between the

Commonsense Knowledge with Negation: A Resource to Enhance Negation Understanding

arXiv:2604.19921v1 Announce Type: new Abstract: Negation is a common and important semantic feature in natural language, yet Large Language Models (LLMs) struggle when negation is involved in natural

Composition-RL: Compose Your Verifiable Prompts for Reinforcement Learning of Large Language Models

arXiv:2602.12036v2 Announce Type: replace Abstract: Large-scale verifiable prompts underpin the success of Reinforcement Learning with Verifiable Rewards (RLVR), but they contain many uninformative ex

Depression Risk Assessment in Social Media via Large Language Models

arXiv:2604.19887v1 Announce Type: cross Abstract: Depression is one of the most prevalent and debilitating mental health conditions worldwide, frequently underdiagnosed and undertreated. The prolifera

Applications

DISCA: A Digital In-memory Stochastic Computing Architecture Using A Compressed Bent-Pyramid Format

arXiv:2511.17265v2 Announce Type: replace-cross Abstract: Nowadays, we are witnessing an Artificial Intelligence revolution that dominates the technology landscape in various application domains, such

applicationsarxiv-cs-ai

DistortBench: Benchmarking Vision Language Models on Image Distortion Identification

arXiv:2604.19966v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used in settings where sensitivity to low-level image degradations matters, including content moderatio

Effects of Cross-lingual Evidence in Multilingual Medical Question Answering

arXiv:2604.20531v1 Announce Type: new Abstract: This paper investigates Multilingual Medical Question Answering across high-resource (English, Spanish, French, Italian) and low-resource (Basque, Kazak

Tutorials

Enhancing ASR Performance in the Medical Domain for Dravidian Languages

arXiv:2604.19797v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) for low-resource Dravidian languages like Telugu and Kannada faces significant challenges in specialized medical do

tutorialsarxiv-cs-ai

Enhancing Research Idea Generation through Combinatorial Innovation and Multi-Agent Iterative Search Strategies

arXiv:2604.20548v1 Announce Type: cross Abstract: Scientific progress depends on the continual generation of innovative re-search ideas. However, the rapid growth of scientific literature has greatly

Evaluating Assurance Cases as Text-Attributed Graphs for Structure and Provenance Analysis

arXiv:2604.20577v1 Announce Type: cross Abstract: An assurance case is a structured argument document that justifies claims about a system's requirements or properties, which are supported by evidence

safetyarxiv-cs-lg

EvolveSignal: A Large Language Model Powered Coding Agent for Discovering Traffic Signal Control Strategies

arXiv:2509.03335v3 Announce Type: replace Abstract: In traffic engineering, fixed-time traffic signal control remains widely used for its low cost, stability, and interpretability. However, its design

agentsarxiv-cs-lg

Formalising the Logit Shift Induced by LoRA: A Technical Note

arXiv:2604.20313v1 Announce Type: cross Abstract: This technical note provides a first-order formalisation of the logit shift and fact-margin change induced by Low-Rank Adaptation (LoRA). Using a firs

Frictionless Love: Associations Between AI Companion Roles and Behavioral Addiction

arXiv:2604.20011v1 Announce Type: cross Abstract: AI companion chatbots increasingly shape how people seek social and emotional connection, sometimes substituting for relationships with romantic partn

From Noise to Signal to Selbstzweck: Reframing Human Label Variation in the Era of Post-training in NLP

arXiv:2510.12817v3 Announce Type: replace-cross Abstract: Human Label Variation (HLV) refers to legitimate disagreement in annotation that reflects the diversity of human perspectives rather than mere