Daily Arxiv

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AnchorDP3: 3D Affordance Guided Sparse Diffusion Policy for Robotic Manipulation

Thought Anchors: Which LLM Reasoning Steps Matter?

Quantifying Fairness in LLMs Beyond Tokens: A Semantic and Statistical Perspective

OmniGen2: Exploration to Advanced Multimodal Generation

Confucius3-Math: A Lightweight High-Performance Reasoning LLM for Chinese K-12 Mathematics Learning

Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models

Quantum-Classical Hybrid Quantized Neural Network

Non-equilibrium Annealed Adjoint Sampler

PP-DocBee2: Improved Baselines with Efficient Data for Multimodal Document Understanding

Mapping the Evolution of Research Contributions using KnoVo

MS-TVNet:A Long-Term Time Series Prediction Method Based on Multi-Scale Dynamic Convolution

No Free Lunch: Rethinking Internal Feedback for LLM Reasoning

TabArena: A Living Benchmark for Machine Learning on Tabular Data

VRAIL: Vectorized Reward-based Attribution for Interpretable Learning

CLAIM: Clinically-Guided LGE Augmentation for Realistic and Diverse Myocardial Scar Synthesis and Segmentation

Screen Hijack: Visual Poisoning of VLM Agents in Mobile Environments

IKDiffuser: A Generative Inverse Kinematics Solver for Multi-arm Robots via Diffusion Model

Fine-Grained Perturbation Guidance via Attention Head Selection

Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning

C3S3: Complementary Competition and Contrastive Selection for Semi-Supervised Medical Image Segmentation

SMAR: Soft Modality-Aware Routing Strategy for MoE-based Multimodal Large Language Models Preserving Language Capabilities

Recycling the Web: A Method to Enhance Pre-training Data Quality and Quantity for Language Models

Supervised Quantum Machine Learning: A Future Outlook from Qubits to Enterprise Applications

Aurora: Are Android Malware Classifiers Reliable and Stable under Distribution Shift?

CogniBench: A Legal-inspired Framework and Dataset for Assessing Cognitive Faithfulness of Large Language Models

AIDRIN 2.0: A Framework to Assess Data Readiness for AI

TSPulse: Dual Space Tiny Pre-Trained Models for Rapid Time-Series Analysis

Teacher Motion Priors: Enhancing Robot Locomotion over Challenging Terrain

WoundAmbit: Bridging State-of-the-Art Semantic Segmentation and Real-World Wound Care

Computation Mechanism Behind LLM Position Generalization

Training Plug-n-Play Knowledge Modules with Deep Context Distillation

MaizeField3D: A Curated 3D Point Cloud and Procedural Model Dataset of Field-Grown Maize from a Diversity Panel

From $\mathcal{O}(n^{2})$ to $\mathcal{O}(n)$ Parameters: Quantum Self-Attention in Vision Transformers for Biomedical Image Classification

Robust Multimodal Learning for Ophthalmic Disease Grading via Disentangled Representation

FGS-SLAM: Fourier-based Gaussian Splatting for Real-time SLAM with Sparse and Dense Map Fusion

Rewarding Graph Reasoning Process makes LLMs more Generalized Reasoners

Protein Structure Tokenization: Benchmarking and New Recipe

Chemical knowledge-informed framework for privacy-aware retrosynthesis learning

Balancing Truthfulness and Informativeness with Uncertainty-Aware Instruction Fine-Tuning

Diffusion Models Through a Global Lens: Are They Culturally Inclusive?

WyckoffDiff -- A Generative Diffusion Model for Crystal Symmetry

Solving Linear-Gaussian Bayesian Inverse Problems with Decoupled Diffusion Sequential Monte Carlo

Adversarial Reasoning at Jailbreaking Time

AgentBreeder: Mitigating the AI Safety Impact of Multi-Agent Scaffolds via Self-Improvement

Rethinking Early Stopping: Refine, Then Calibrate

Unlocking In-Context Learning for Natural Datasets Beyond Language Modelling

Towards Backdoor Stealthiness in Model Parameter Space

Distributed satellite information networks: Architecture, enabling technologies, and trends

Integrating Various Software Artifacts for Better LLM-based Bug Localization and Program Repair

Proximal Control of UAVs with Federated Learning for Human-Robot Collaborative Domains

Understanding World or Predicting Future? A Comprehensive Survey of World Models

USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting

Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers

Toddlers' Active Gaze Behavior Supports Self-Supervised Object Learning

ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model

Fuzz-Testing Meets LLM-Based Agents: An Automated and Efficient Framework for Jailbreaking Text-To-Image Generation Models

Evaluating Long Range Dependency Handling in Code Generation LLMs

Physics-informed Imitative Reinforcement Learning for Real-world Driving

COBRA-PPM: A Causal Bayesian Reasoning Architecture Using Probabilistic Programming for Robot Manipulation Under Uncertainty

FluoroSAM: A Language-promptable Foundation Model for Flexible X-ray Image Segmentation

Do Concept Bottleneck Models Respect Localities?

When Large Language Models contradict humans? Large Language Models' Sycophantic Behaviour

Low-light Pedestrian Detection in Visible and Infrared Image Feeds: Issues and Challenges

A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges

PhysUniBench: An Undergraduate-Level Physics Reasoning Benchmark for Multimodal Models

Evaluating Generalization and Representation Stability in Small LMs via Prompting, Fine-Tuning and Out-of-Distribution Prompts

Scientists' First Exam: Probing Cognitive Abilities of MLLM via Perception, Understanding, and Reasoning

The Alignment Trap: Complexity Barriers

The State of Large Language Models for African Languages: Progress and Challenges

Hybrid AI for Responsive Multi-Turn Online Conversations with Novel Dynamic Routing and Feedback Adaptation

Turing Test 2.0: The General Intelligence Threshold

$C^3$-Bench: The Things Real Disturbing LLM based Agent in Multi-Tasking

RefPentester: A Knowledge-Informed Self-Reflective Penetration Testing Framework Based on Large Language Models

Fine, I'll Merge It Myself: A Multi-Fidelity Framework for Automated Model Merging

Towards Better Benchmark Datasets for Inductive Knowledge Graph Completion

Inside you are many wolves: Using cognitive models to interpret value trade-offs in LLMs

Disentangled representations of microscopy images

Define-ML: An Approach to Ideate Machine Learning-Enabled Systems

Weighted Mean Frequencies: a handcraft Fourier feature for 4D Flow MRI segmentation

Deciphering GunType Hierarchy through Acoustic Analysis of Gunshot Recordings

AI in the Writing Process: How Purposeful AI Support Fosters Student Writing

Dense Video Captioning using Graph-based Sentence Summarization

Causal Representation Learning with Observational Grouping for CXR Classification

Vulnerability Disclosure through Adaptive Black-Box Adversarial Attacks on NIDS

Show, Tell and Summarize: Dense Video Captioning Using Visual Cue Aided Sentence Summarization

DeepQuark: deep-neural-network approach to multiquark bound states

Large Language Model-Driven Code Compliance Checking in Building Information Modeling

Pay Less Attention to Deceptive Artifacts: Robust Detection of Compressed Deepfakes on Online Social Networks

When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs

WattsOnAI: Measuring, Analyzing, and Visualizing Energy and Carbon Footprint of AI Workloads

Industrial Energy Disaggregation with Digital Twin-generated Dataset and Efficient Data Augmentation

OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling

ReCode: Updating Code API Knowledge with Reinforcement Learning

Counterfactual Influence as a Distributional Quantity

Automatic Demonstration Selection for LLM-based Tabular Data Classification

An Agentic System for Rare Disease Diagnosis with Traceable Reasoning

Off-Policy Evaluation and Learning for the Future under Non-Stationarity

SV-LLM: An Agentic Approach for SoC Security Verification using Large Language Models

Client Clustering Meets Knowledge Sharing: Enhancing Privacy and Robustness in Personalized Peer-to-Peer Learning

CARMA: Context-Aware Situational Grounding of Human-Robot Group Interactions by Combining Vision-Language Models with Object and Action Recognition

CogniBench: A Legal-inspired Framework and Dataset for Assessing Cognitive Faithfulness of Large Language Models

Created by

Haebom

저자

Xiaqiang Tang, Jian Li, Keyu Hu, Du Nan, Xiaolong Li, Xi Zhang, Weigao Sun, Sihong Xie

개요

대규모 언어 모델(LLM)이 제공된 맥락을 뒷받침하지 않는 주장인 신뢰성 환각(Faithfulness hallucinations)을 다룬다. 기존 벤치마크는 출처 자료를 바꿔 말하는 "사실적 진술"에 초점을 맞추고 주어진 맥락으로부터 추론을 포함하는 "인지적 진술"을 간과하여 인지적 진술의 환각을 평가하고 탐지하는 것이 어렵다는 점을 지적한다. 법적 영역에서 증거를 평가하는 방식에서 영감을 얻어 인지적 진술의 신뢰성 수준을 평가하는 엄격한 프레임워크를 설계하고, 통찰력 있는 통계를 보여주는 CogniBench 데이터셋을 소개한다. 빠르게 발전하는 LLM에 발맞추어 다양한 모델에 쉽게 확장할 수 있는 자동 주석 파이프라인을 개발하여, 사실적 및 인지적 환각 모두에 대한 정확한 검출기를 훈련하는 데 도움이 되는 대규모 CogniBench-L 데이터셋을 생성한다. 모델과 데이터셋은 https://github.com/FUTUREEEEEE/CogniBench 에서 공개한다.

GitHub - FUTUREEEEEE/CogniBench: ACL 2025: CogniBench: A Legal-inspired Framework and Dataset for Assessing Cognitive Faithfulness of Large Language Models

ACL 2025: CogniBench: A Legal-inspired Framework and Dataset for Assessing Cognitive Faithfulness of Large Language Models - FUTUREEEEEE/CogniBench

시사점, 한계점

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시사점: 법적 영역의 증거 평가 방식을 활용하여 LLM의 인지적 진술 신뢰성 평가 프레임워크를 제시하고, 대규모 데이터셋(CogniBench, CogniBench-L)을 구축하여 사실적 및 인지적 환각 검출기 훈련을 지원한다. 자동 주석 파이프라인을 통해 지속적인 데이터 확보 및 모델 개선이 가능하다.

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한계점: 제시된 프레임워크와 데이터셋의 일반화 가능성 및 다양한 LLM에 대한 적용 가능성에 대한 추가적인 검증이 필요하다. 인지적 진술의 신뢰성 평가 기준의 객관성 및 주관성 문제에 대한 논의가 부족할 수 있다. 자동 주석 파이프라인의 정확도와 한계에 대한 자세한 분석이 필요하다.

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