Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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VideoPDE: Unified Generative PDE Solving via Video Inpainting Diffusion Models

Prefix-Tuning+: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention

Graph-Convolutional-Beta-VAE for Synthetic Abdominal Aorta Aneurysm Generation

A Production Scheduling Framework for Reinforcement Learning Under Real-World Constraints

ROSAQ: Rotation-based Saliency-Aware Weight Quantization for Efficiently Compressing Large Language Models

Seewo's Submission to MLC-SLM: Lessons learned from Speech Reasoning Language Models

SeqPE: Transformer with Sequential Position Encoding

No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need!

AI-Facilitated Analysis of Abstracts and Conclusions: Flagging Unsubstantiated Claims and Ambiguous Pronouns

IKDiffuser: Fast and Diverse Inverse Kinematics Solution Generation for Multi-arm Robotic Systems

Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark

Deep Learning Model Acceleration and Optimization Strategies for Real-Time Recommendation Systems

Adaptive Composition of Machine Learning as a Service (MLaaS) for IoT Environments

Discrete Audio Tokens: More Than a Survey!

FlagEvalMM: A Flexible Framework for Comprehensive Multimodal Model Evaluation

Inherently Faithful Attention Maps for Vision Transformers

Reparameterized LLM Training via Orthogonal Equivalence Transformation

MultiMatch: Multihead Consistency Regularization Matching for Semi-Supervised Text Classification

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms

CellCLIP -- Learning Perturbation Effects in Cell Painting via Text-Guided Contrastive Learning

EuroLLM-9B: Technical Report

Incentivizing Reasoning for Advanced Instruction-Following of Large Language Models

EEG2TEXT-CN: An Exploratory Study of Open-Vocabulary Chinese Text-EEG Alignment via Large Language Model and Contrastive Learning on ChineseEEG

MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning

CSVQA: A Chinese Multimodal Benchmark for Evaluating STEM Reasoning Capabilities of VLMs

KGMark: A Diffusion Watermark for Knowledge Graphs

Representing local protein environments with atomistic foundation models

Accelerating RLHF Training with Reward Variance Increase

FlowAlign: Trajectory-Regularized, Inversion-Free Flow-based Image Editing

PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation

REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning

MSVIT: Improving Spiking Vision Transformer Using Multi-scale Attention Fusion

Abacus: A Cost-Based Optimizer for Semantic Operator Systems

IP Leakage Attacks Targeting LLM-Based Multi-Agent Systems

CAPTURE: Context-Aware Prompt Injection Testing and Robustness Enhancement

Chatting with Papers: A Hybrid Approach Using LLMs and Knowledge Graphs

Patho-R1: A Multimodal Reinforcement Learning-Based Pathology Expert Reasoner

LongCodeBench: Evaluating Coding LLMs at 1M Context Windows

H$^3$DP: Triply-Hierarchical Diffusion Policy for Visuomotor Learning

Convert Language Model into a Value-based Strategic Planner

Graph RAG for Legal Norms: A Hierarchical, Temporal and Deterministic Approach

CAPO: Cost-Aware Prompt Optimization

Spatiotemporal Learning of Brain Dynamics from fMRI Using Frequency-Specific Multi-Band Attention for Cognitive and Psychiatric Applications

The Backfiring Effect of Weak AI Safety Regulation

Assessing Consistency and Reproducibility in the Outputs of Large Language Models: Evidence Across Diverse Finance and Accounting Tasks

Achieving Unbiased Multi-Instance Learning via Balanced Fine-Grained Positive-Unlabeled Learning

Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regression

SOPBench: Evaluating Language Agents at Following Standard Operating Procedures and Constraints

Effect of Selection Format on LLM Performance

Reward Shaping to Mitigate Reward Hacking in RLHF

SAE-V: Interpreting Multimodal Models for Enhanced Alignment

LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification

Target Speaker Extraction through Comparing Noisy Positive and Negative Audio Enrollments

Hardware-Friendly Static Quantization Method for Video Diffusion Transformers

PredictaBoard: Benchmarking LLM Score Predictability

Towards Geo-Culturally Grounded LLM Generations

Diverse Topology Optimization using Modulated Neural Fields

Counterfactual-Consistency Prompting for Relative Temporal Understanding in Large Language Models

NAROCE: A Neural Algorithmic Reasoner Framework for Online Complex Event Detection

Bridging Voting and Deliberation with Algorithms: Field Insights from vTaiwan and Kultur Komitee

From tools to thieves: Measuring and understanding public perceptions of AI through crowdsourced metaphors

The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs

Language and Planning in Robotic Navigation: A Multilingual Evaluation of State-of-the-Art Models

Agent Laboratory: Using LLM Agents as Research Assistants

LLMs Help Alleviate the Cross-Subject Variability in Brain Signal and Language Alignment

Uncertainty-Aware Critic Augmentation for Hierarchical Multi-Agent EV Charging Control

Parallel Greedy Best-First Search with a Bound on Expansions Relative to Sequential Search

PunchBench: Benchmarking MLLMs in Multimodal Punchline Comprehension

BESSTIE: A Benchmark for Sentiment and Sarcasm Classification for Varieties of English

LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior

Geometric Signatures of Compositionality Across a Language Model's Lifetime

AssistantX: An LLM-Powered Proactive Assistant in Collaborative Human-Populated Environment

MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided Prototyping

What is the Right Notion of Distance between Predict-then-Optimize Tasks?

QuantFactor REINFORCE: Mining Steady Formulaic Alpha Factors with Variance-bounded REINFORCE

MALSIGHT: Exploring Malicious Source Code and Benign Pseudocode for Iterative Binary Malware Summarization

Bridging Social Media and Search Engines: Dredge Words and the Detection of Unreliable Domains

Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAG

Quality-aware Masked Diffusion Transformer for Enhanced Music Generation

InkSight: Offline-to-Online Handwriting Conversion by Teaching Vision-Language Models to Read and Write

Exploring news intent and its application: A theory-driven approach

Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures

AgentOrchestra: A Hierarchical Multi-Agent Framework for General-Purpose Task Solving

ConsistencyChecker: Tree-based Evaluation of LLM Generalization Capabilities

A Conjecture on a Fundamental Trade-Off between Certainty and Scope in Symbolic and Generative AI

Comment on The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

TIP-Search: Time-Predictable Inference Scheduling for Market Prediction under Uncertain Load

AgentCPM-GUI: Building Mobile-Use Agents with Reinforcement Fine-Tuning

Large Language Models' Reasoning Stalls: An Investigation into the Capabilities of Frontier Models

OrgAccess: A Benchmark for Role Based Access Control in Organization Scale LLMs

SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning

Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis

Arbitrarily Applicable Same/Opposite Relational Responding with NARS

ShorterBetter: Guiding Reasoning Models to Find Optimal Inference Length for Efficient Reasoning

Behaviour Discovery and Attribution for Explainable Reinforcement Learning

Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible

Chain-of-Thought Reasoning In The Wild Is Not Always Faithful

Activation Space Interventions Can Be Transferred Between Large Language Models

Planning of Heuristics: Strategic Planning on Large Language Models with Monte Carlo Tree Search for Automating Heuristic Optimization

MAGELLAN: Metacognitive predictions of learning progress guide autotelic LLM agents in large goal spaces

What is the Right Notion of Distance between Predict-then-Optimize Tasks?

Created by

Haebom

저자

Paula Rodriguez-Diaz, Lingkai Kong, Kai Wang, David Alvarez-Melis, Milind Tambe

개요

본 논문은 Predict-then-Optimize (PtO) 프레임워크에서의 데이터셋 비교를 위한 새로운 거리 측정 방식인 OTD³(Optimal Transport Decision-aware Dataset Distance)를 제안합니다. 기존의 데이터셋 거리 측정 방식은 예측 오류 최소화에 초점을 맞춘 반면, OTD³는 특징과 레이블뿐만 아니라 downstream 의사결정까지 고려하여 데이터셋 간 유사성을 측정합니다. 논문에서는 OTD³가 기존 방식보다 PtO 설정에서 모델 적응 성공 여부를 더 효과적으로 포착하며, OTD³ 기반의 PtO 특화 적응 경계를 도출합니다. 실험적으로 세 가지 서로 다른 PtO 작업에 대한 모델 전이성을 정확하게 예측하는 것을 보여줍니다.

시사점, 한계점

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시사점:

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PtO 프레임워크에서 데이터셋 유사성을 평가하는 새로운 방법론 제시

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기존 방식의 한계를 극복하고 downstream 의사결정을 고려한 더 정확한 데이터셋 거리 측정 가능

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OTD³ 기반의 PtO 특화 적응 경계 도출을 통한 이론적 기반 마련

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다양한 PtO 작업에서 OTD³의 효과적인 모델 전이성 예측 성능 검증

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공개된 코드를 통해 재현성 및 확장성 확보

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한계점:

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제안된 방법론의 성능은 특정 PtO 작업에 국한될 수 있음

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OTD³ 계산의 계산 복잡도가 높을 수 있음

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다양한 데이터셋 및 PtO 작업에 대한 추가적인 실험이 필요함

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