Daily Arxiv

世界中で発行される人工知能関連の論文をまとめるページです。
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論文の著作権は著者および関連機関にあり、共有する際は出典を明記してください。

CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics

Ada-TransGNN: An Air Quality Prediction Model Based On Adaptive Graph Convolutional Networks

Unlearning as Ablation: Toward a Falsifiable Benchmark for Generative Scientific Discovery

Consistent Opponent Modeling of Static Opponents in Imperfect-Information Games

Finding Outliers in a Haystack: Anomaly Detection for Large Pointcloud Scenes

Agentic AI for Software: thoughts from Software Engineering community

Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMs

Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning

Dream to Chat: Model-based Reinforcement Learning on Dialogues with User Belief Modeling

A Survey of Threats Against Voice Authentication and Anti-Spoofing Systems

Generative Artificial Intelligence and Agents in Research and Teaching

CALR: Corrective Adaptive Low-Rank Decomposition for Efficient Large Language Model Layer Compression

Comparative Analysis of UAV Path Planning Algorithms for Efficient Navigation in Urban 3D Environments

Retrieval Enhanced Feedback via In-context Neural Error-book

From Confidence to Collapse in LLM Factual Robustness

On Task Vectors and Gradients

Learning in Repeated Multi-Objective Stackelberg Games with Payoff Manipulation

NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model

DLLMQuant: Quantizing Diffusion-based Large Language Models

LLM-Enhanced Linear Autoencoders for Recommendation

Leveraging GNN to Enhance MEF Method in Predicting ENSO

Uncertainty-Guided Face Matting for Occlusion-Aware Face Transformation

New Kid in the Classroom: Exploring Student Perceptions of AI Coding Assistants

Large Language Model-Based Framework for Explainable Cyberattack Detection in Automatic Generation Control Systems

SKA-Bench: A Fine-Grained Benchmark for Evaluating Structured Knowledge Understanding of LLMs

Apple Intelligence Foundation Language Models: Tech Report 2025

SE-VLN: A Self-Evolving Vision-Language Navigation Framework Based on Multimodal Large Language Models

Demographic-aware fine-grained classification of pediatric wrist fractures

Krul: Efficient State Restoration for Multi-turn Conversations with Dynamic Cross-layer KV Sharing

Solar Altitude Guided Scene Illumination

An Agentic System for Rare Disease Diagnosis with Traceable Reasoning

Spectra-to-Structure and Structure-to-Spectra Inference Across the Periodic Table

UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation

Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models

EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion

RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection

Revisiting SSL for sound event detection: complementary fusion and adaptive post-processing

Concept-Guided Interpretability via Neural Chunking

Unveiling the Landscape of LLM Deployment in the Wild: An Empirical Study

An Ontology-Driven Graph RAG for Legal Norms: A Hierarchical, Temporal, and Deterministic Approach

Prefill-level Jailbreak: A Black-Box Risk Analysis of Large Language Models

Video CLIP Model for Multi-View Echocardiography Interpretation

A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Disease Detection from Retinal Fundus Images

M$^2$IV: Towards Efficient and Fine-grained Multimodal In-Context Learning via Representation Engineering

Noise-based reward-modulated learning

Faster Parameter-Efficient Tuning with Token Redundancy Reduction

UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials

Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems

Large Language Models Badly Generalize across Option Length, Problem Types, and Irrelevant Noun Replacements

TableTalk: Scaffolding Spreadsheet Development with a Language Agent

StagFormer: Time Staggering Transformer Decoding for RunningLayers In Parallel

Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis

Generative Artificial Intelligence-Supported Pentesting: A Comparison between Claude Opus, GPT-4, and Copilot

Safe Multiagent Coordination via Entropic Exploration

TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use

Cultural Dimensions of AI Perception: Charting Expectations, Risks, Benefits, Tradeoffs, and Value in Germany and China

CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solvers

Perception Gaps in Risk, Benefit, and Value Between Experts and Public Challenge Socially Accepted AI

Hierarchical Object-Oriented POMDP Planning for Object Rearrangement

From Intents to Conversations: Generating Intent-Driven Dialogues with Contrastive Learning for Multi-Turn Classification

Secure Reinforcement Learning via Shuffle Privacy Model

Overcoming label shift with target-aware federated learning

Benchmarking XAI Explanations with Human-Aligned Evaluations

HonestCyberEval: An AI Cyber Risk Benchmark for Automated Software Exploitation

Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning

GeNet: A Multimodal LLM-Based Co-Pilot for Network Topology and Configuration

ChatGPT Doesn't Trust Chargers Fans: Guardrail Sensitivity in Context

Ego-Foresight: Self-supervised Learning of Agent-Aware Representations for Improved RL

Exploring the Robustness of Language Models for Tabular Question Answering via Attention Analysis

Learning county from pixels: corn yield prediction with attention-weighted multiple instance learning

Memory augment is All You Need for image restoration

Rethinking Distribution Shifts: Empirical Analysis and Inductive Modeling for Tabular Data

DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models

Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles

Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing

ST-Raptor: LLM-Powered Semi-Structured Table Question Answering

Route-and-Execute: Auditable Model-Card Matching and Specialty-Level Deployment

LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence

Response and Prompt Evaluation to Prevent Parasocial Relationships with Chatbots

Profile-Aware Maneuvering: A Dynamic Multi-Agent System for Robust GAIA Problem Solving by AWorld

Multi-Agent LLMs as Ethics Advocates for AI-Based Systems

Feature-Guided Neighbor Selection for Non-Expert Evaluation of Model Predictions

Architecting Clinical Collaboration: Multi-Agent Reasoning Systems for Multimodal Medical VQA

MRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation

Jigsaw-Puzzles: From Seeing to Understanding to Reasoning in Vision-Language Models

The Influence of Human-inspired Agentic Sophistication in LLM-driven Strategic Reasoners

YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models

Consensus in Motion: A Case of Dynamic Rationality of Sequential Learning in Probability Aggregation

Can Large Language Models Act as Ensembler for Multi-GNNs?

Pessimistic Iterative Planning with RNNs for Robust POMDPs

Safe Reinforcement Learning in Black-Box Environments via Adaptive Shielding

Integrating Large Language Model for Improved Causal Discovery

A Survey on Causal Discovery: Theory and Practice

Generative Interfaces for Language Models

Interpolating Speaker Identities in Embedding Space for Data Expansion

VibeVoice Technical Report

LSD-3D: Large-Scale 3D Driving Scene Generation with Geometry Grounding

Understanding Tool-Integrated Reasoning

Emotions as Ambiguity-aware Ordinal Representations

Real-Time Model Checking for Closed-Loop Robot Reactive Planning

CALR: Corrective Adaptive Low-Rank Decomposition for Efficient Large Language Model Layer Compression

Created by

Haebom

作者

Muchammad Daniyal Kautsar, Afra Majida Hariono, Widyawan, Syukron Abu Ishaq Alfarozi, Kuntpong Woraratpanya

概要

本論文では、大規模言語モデル（LLM）の展開に伴う困難、特にモデルの膨大なサイズと高い計算要求問題を解決するために、特異値分解（SVD）を用いた低ランク分解技術を改善する新しい方法であるCorrective Adaptive Low-Rank Decomposition（CALR）を提案します。従来のSVDベースの圧縮方法は、モデルの再構築誤差を最小限に抑えることに焦点を当てて機能的性能の低下を招きますが、CALRはSVDで圧縮された階層と機能的残差誤差を回復するために学習された並列低ランク補正モジュールを組み合わせることによってこの問題を解決します。 SmolLM2-135M、Qwen3-0.6B、Llama-3.2-1Bなどのモデルに対する実験結果、CALRはパラメータ数を26.93% 51.77%減少させながら元のモデル性能の59.45% 90.42%を維持し、従来のLaCo、ShortGPT、LoSparseなど。これは、機能的な情報損失を学習可能な信号として扱うことが有効な圧縮パラダイムであることを示している。

Takeaways、Limitations

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Takeaways:

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機能的情報損失を学習可能な信号として扱う新しい圧縮パラダイムの提示

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従来の低ランク分解技術より優れた性能を示すCALRアルゴリズムの開発

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LLMのサイズと計算要件の削減による実環境展開の可能性の向上

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資源制約環境におけるLLMの利用可能性の拡大

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Limitations:

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提示された実験結果は特定のモデルに限定され、一般化の可能性に関するさらなる研究が必要

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CALRの校正モジュールの学習に必要な計算コストと時間の分析が必要

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さまざまなサイズおよび種類のLLMのための追加の実験および性能評価が必要

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