Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
본 페이지는 Google Gemini를 활용해 요약 정리하며, 비영리로 운영 됩니다.
논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

Surgical Agent Orchestration Platform for Voice-directed Patient Data Interaction

FinRpt: Dataset, Evaluation System and LLM-based Multi-agent Framework for Equity Research Report Generation

Hard vs. Noise: Resolving Hard-Noisy Sample Confusion in Recommender Systems via Large Language Models

Learning Quantized Continuous Controllers for Integer Hardware

Differentiated Directional Intervention A Framework for Evading LLM Safety Alignment

TiS-TSL: Image-Label Supervised Surgical Video Stereo Matching via Time-Switchable Teacher-Student Learning

Active Learning for Animal Re-Identification with Ambiguity-Aware Sampling

Transolver is a Linear Transformer: Revisiting Physics-Attention through the Lens of Linear Attention

Exploiting Inter-Session Information with Frequency-enhanced Dual-Path Networks for Sequential Recommendation

SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?

A Remarkably Efficient Paradigm to Multimodal Large Language Models for Sequential Recommendation

EndoIR: Degradation-Agnostic All-in-One Endoscopic Image Restoration via Noise-Aware Routing Diffusion

Enhancing Diffusion Model Guidance through Calibration and Regularization

DRAGON: Guard LLM Unlearning in Context via Negative Detection and Reasoning

Report from Workshop on Dialogue alongside Artificial Intelligence

Token Is All You Need: Cognitive Planning through Belief-Intent Co-Evolution

Selective Diabetic Retinopathy Screening with Accuracy-Weighted Deep Ensembles and Entropy-Guided Abstention

SWE-Compass: Towards Unified Evaluation of Agentic Coding Abilities for Large Language Models

Alternative Fairness and Accuracy Optimization in Criminal Justice

I Detect What I Don't Know: Incremental Anomaly Learning with Stochastic Weight Averaging-Gaussian for Oracle-Free Medical Imaging

OMPILOT: Harnessing Transformer Models for Auto Parallelization to Shared Memory Computing Paradigms

Federated Learning with Gramian Angular Fields for Privacy-Preserving ECG Classification on Heterogeneous IoT Devices

How to Evaluate Speech Translation with Source-Aware Neural MT Metrics

GUI-AIMA: Aligning Intrinsic Multimodal Attention with a Context Anchor for GUI Grounding

Normalization in Attention Dynamics

Preference-based Reinforcement Learning beyond Pairwise Comparisons: Benefits of Multiple Options

Language over Content: Tracing Cultural Understanding in Multilingual Large Language Models

TACL: Threshold-Adaptive Curriculum Learning Strategy for Enhancing Medical Text Understanding

TraceCoder: Towards Traceable ICD Coding via Multi-Source Knowledge Integration

Bee: A High-Quality Corpus and Full-Stack Suite to Unlock Advanced Fully Open MLLMs

Comparative Analysis of Large Language Models for the Machine-Assisted Resolution of User Intentions

Evolutionary Profiles for Protein Fitness Prediction

Epistemic Diversity and Knowledge Collapse in Large Language Models

MENLO: From Preferences to Proficiency -- Evaluating and Modeling Native-like Quality Across 47 Languages

Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy

CyberSOCEval: Benchmarking LLMs Capabilities for Malware Analysis and Threat Intelligence Reasoning

A Realistic Evaluation of Cross-Frequency Transfer Learning and Foundation Forecasting Models

TimeMosaic: Temporal Heterogeneity Guided Time Series Forecasting via Adaptive Granularity Patch and Segment-wise Decoding

RSVG-ZeroOV: Exploring a Training-Free Framework for Zero-Shot Open-Vocabulary Visual Grounding in Remote Sensing Images

Instance Generation for Meta-Black-Box Optimization through Latent Space Reverse Engineering

Decoding Latent Attack Surfaces in LLMs: Prompt Injection via HTML in Web Summarization

Towards Methane Detection Onboard Satellites

OPERA: A Reinforcement Learning--Enhanced Orchestrated Planner-Executor Architecture for Reasoning-Oriented Multi-Hop Retrieval

Can LLM-Generated Textual Explanations Enhance Model Classification Performance? An Empirical Study

Towards Embodied Agentic AI: Review and Classification of LLM- and VLM-Driven Robot Autonomy and Interaction

CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis

Beyond Algorethics: Addressing the Ethical and Anthropological Challenges of AI Recommender Systems

Imbalance in Balance: Online Concept Balancing in Generation Models

ReCode: Updating Code API Knowledge with Reinforcement Learning

Rethinking Losses for Diffusion Bridge Samplers

Zeroth-Order Optimization Finds Flat Minima

UniSite: The First Cross-Structure Dataset and Learning Framework for End-to-End Ligand Binding Site Detection

A Unified and Fast-Sampling Diffusion Bridge Framework via Stochastic Optimal Control

BroadGen: A Framework for Generating Effective and Efficient Advertiser Broad Match Keyphrase Recommendations

FB-RAG: Improving RAG with Forward and Backward Lookup

FedSEA-LLaMA: A Secure, Efficient and Adaptive Federated Splitting Framework for Large Language Models

Policy-Driven World Model Adaptation for Robust Offline Model-based Reinforcement Learning

RL in Name Only? Analyzing the Structural Assumptions in RL post-training for LLMs

Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors

Tool-Aided Evolutionary LLM for Generative Policy Toward Efficient Resource Management in Wireless Federated Learning

FALCON: False-Negative Aware Learning of Contrastive Negatives in Vision-Language Alignment

How Hungry is AI? Benchmarking Energy, Water, and Carbon Footprint of LLM Inference

FaSDiff: Balancing Perception and Semantics in Face Compression via Stable Diffusion Priors

On the generalization of language models from in-context learning and finetuning: a controlled study

Enhancing Speech-to-Speech Dialogue Modeling with End-to-End Retrieval-Augmented Generation

A Multimodal Recaptioning Framework to Account for Perceptual Diversity Across Languages in Vision-Language Modeling

WildFireCan-MMD: A Multimodal Dataset for Classification of User-Generated Content During Wildfires in Canada

MULTI-LF: A Continuous Learning Framework for Real-Time Malicious Traffic Detection in Multi-Environment Networks

STAR-1: Safer Alignment of Reasoning LLMs with 1K Data

COPA: Comparing the incomparable in multi-objective model evaluation

CLEV: LLM-Based Evaluation Through Lightweight Efficient Voting for Free-Form Question-Answering

Towards Synthesizing High-Dimensional Tabular Data with Limited Samples

Explaining the Unexplainable: A Systematic Review of Explainable AI in Finance

Learning Vision-Based Neural Network Controllers with Semi-Probabilistic Safety Guarantees

MA-GTS: A Multi-Agent Framework for Solving Complex Graph Problems in Real-World Applications

On the Convergence and Stability of Upside-Down Reinforcement Learning, Goal-Conditioned Supervised Learning, and Online Decision Transformers

A Multi-Agent Conversational Bandit Approach to Online Evaluation and Selection of User-Aligned LLM Responses

Generalizing Weisfeiler-Lehman Kernels to Subgraphs

SCoTT: Strategic Chain-of-Thought Tasking for Wireless-Aware Robot Navigation in Digital Twins

GeMID: Generalizable Models for IoT Device Identification

Flash Inference: Near Linear Time Inference for Long Convolution Sequence Models and Beyond

Bayes Adaptive Monte Carlo Tree Search for Offline Model-based Reinforcement Learning

Selection of LLM Fine-Tuning Data based on Orthogonal Rules

Benchmarking Domain Generalization Algorithms in Computational Pathology

Reference-Guided Verdict: LLMs-as-Judges in Automatic Evaluation of Free-Form QA

Identifying treatment response subgroups in observational time-to-event data

Informed Correctors for Discrete Diffusion Models

Integrating Artificial Intelligence into Operating Systems: A Survey on Techniques, Applications, and Future Directions

Multimodal Adversarial Defense for Vision-Language Models by Leveraging One-To-Many Relationships

Spikingformer: A Key Foundation Model for Spiking Neural Networks

DeepPersona: A Generative Engine for Scaling Deep Synthetic Personas

Two Heads are Better than One: Distilling Large Language Model Features Into Small Models with Feature Decomposition and Mixture

A Theoretical Analysis of Detecting Large Model-Generated Time Series

Green AI: A systematic review and meta-analysis of its definitions, lifecycle models, hardware and measurement attempts

Spilling the Beans: Teaching LLMs to Self-Report Their Hidden Objectives

Reasoning with Confidence: Efficient Verification of LLM Reasoning Steps via Uncertainty Heads

When Object-Centric World Models Meet Policy Learning: From Pixels to Policies, and Where It Breaks

ScRPO: From Errors to Insights

Deep Value Benchmark: Measuring Whether Models Generalize Deep Values or Shallow Preferences

Glia: A Human-Inspired AI for Automated Systems Design and Optimization

SPHERE: An Evaluation Card for Human-AI Systems

Created by

Haebom

저자

Qianou Ma, Dora Zhao, Xinran Zhao, Chenglei Si, Chenyang Yang, Ryan Louie, Ehud Reiter, Diyi Yang, Tongshuang Wu

개요

본 논문은 대규모 언어 모델(LLM) 시대에 다양한 인간-AI 상호작용 시스템에 대한 효과적인 평가 방법과 표준을 수립하는 어려움을 다룹니다. 더 투명한 문서화를 장려하고 인간-AI 시스템 평가 설계 옵션에 대한 논의를 촉진하기 위해, 다섯 가지 주요 차원(1. 평가 대상, 2. 평가 방법, 3. 평가 참여자, 4. 평가 시점, 5. 평가 검증 방법)을 포함하는 SPHERE 평가 카드를 제시합니다. 39개의 인간-AI 시스템에 대한 SPHERE를 이용한 검토를 수행하여 현재 평가 관행과 개선 영역을 제시하고, 평가 관행의 타당성과 엄격성을 개선하기 위한 세 가지 권장 사항을 제공합니다.

시사점, 한계점

•

시사점:

◦

인간-AI 상호작용 시스템 평가를 위한 체계적인 프레임워크(SPHERE) 제공

◦

기존 평가 관행의 문제점과 개선 방향 제시

◦

평가의 타당성 및 엄격성 향상을 위한 구체적인 권장 사항 제시

◦

더 투명하고 체계적인 인간-AI 시스템 평가를 위한 논의 촉진

•

한계점:

◦

SPHERE 카드의 보편적인 적용 가능성 및 효용성에 대한 추가적인 검증 필요

◦

제시된 권장 사항의 실제 적용 가능성 및 효과에 대한 후속 연구 필요

◦

분석 대상 시스템의 수(39개)가 상대적으로 적을 수 있음

◦

특정 유형의 인간-AI 시스템에 편향된 평가일 가능성 존재

Made with Slashpage