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.

Distillation Robustifies Unlearning

Cartridges: Lightweight and general-purpose long context representations via self-study

Text-to-LoRA: Instant Transformer Adaption

Information Bargaining: Bilateral Commitment in Bayesian Persuasion

Cross-lingual Collapse: How Language-Centric Foundation Models Shape Reasoning in Large Language Models

Heartcare Suite: Multi-dimensional Understanding of ECG with Raw Multi-lead Signal Modeling

Peer-Ranked Precision: Creating a Foundational Dataset for Fine-Tuning Vision Models from DataSeeds' Annotated Imagery

TissUnet: Improved Extracranial Tissue and Cranium Segmentation for Children through Adulthood

A Red Teaming Roadmap Towards System-Level Safety

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Context Is Not Comprehension

Feature-Based Lie Group Transformer for Real-World Applications

Horizon Reduction Makes RL Scalable

SLAC: Simulation-Pretrained Latent Action Space for Whole-Body Real-World RL

A Diffusion-Driven Temporal Super-Resolution and Spatial Consistency Enhancement Framework for 4D MRI imaging

BiMa: Towards Biases Mitigation for Text-Video Retrieval via Scene Element Guidance

Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds

Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO AMD Progression Challenge

CoT is Not True Reasoning, It Is Just a Tight Constraint to Imitate: A Theory Perspective

Rethinking the effects of data contamination in Code Intelligence

MINT: Multimodal Instruction Tuning with Multimodal Interaction Grouping

Protap: A Benchmark for Protein Modeling on Realistic Downstream Applications

NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction

SATA-BENCH: Select All That Apply Benchmark for Multiple Choice Questions

Learning from Double Positive and Unlabeled Data for Potential-Customer Identification

Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race

Diversity of Transformer Layers: One Aspect of Parameter Scaling Laws

Noise-Robustness Through Noise: Asymmetric LoRA Adaption with Poisoning Expert

Large Language Models Often Know When They Are Being Evaluated

WorkForceAgent-R1: Incentivizing Reasoning Capability in LLM-based Web Agents via Reinforcement Learning

CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation

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

RainFusion: Adaptive Video Generation Acceleration via Multi-Dimensional Visual Redundancy

VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verification

Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles

APE: Selective Fine-tuning with Acceptance Criteria for Language Model Adaptation

When Two LLMs Debate, Both Think They'll Win

Turb-L1: Achieving Long-term Turbulence Tracing By Tackling Spectral Bias

GRE Suite: Geo-localization Inference via Fine-Tuned Vision-Language Models and Enhanced Reasoning Chains

Can MLLMs Guide Me Home? A Benchmark Study on Fine-Grained Visual Reasoning from Transit Maps

Sample Complexity of Diffusion Model Training Without Empirical Risk Minimizer Access

EVADE: Multimodal Benchmark for Evasive Content Detection in E-Commerce Applications

Simulating Macroeconomic Expectations using LLM Agents

Mixture of Decoding: An Attention-Inspired Adaptive Decoding Strategy to Mitigate Hallucinations in Large Vision-Language Models

Mechanistic evaluation of Transformers and state space models

Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models

Pel, A Programming Language for Orchestrating AI Agents

MARVEL: Multi-Agent RTL Vulnerability Extraction using Large Language Models

Learning Pareto-Optimal Rewards from Noisy Preferences: A Framework for Multi-Objective Inverse Reinforcement Learning

Q-Policy: Quantum-Enhanced Policy Evaluation for Scalable Reinforcement Learning

BLEUBERI: BLEU is a surprisingly effective reward for instruction following

Position: We Need Responsible, Application-Driven (RAD) AI Research

Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach

LookAlike: Consistent Distractor Generation in Math MCQs

Tree-Sliced Wasserstein Distance with Nonlinear Projection

Test-time Correlation Alignment

Pushing the Limits of Low-Bit Optimizers: A Focus on EMA Dynamics

OpenTCM: A GraphRAG-Empowered LLM-based System for Traditional Chinese Medicine Knowledge Retrieval and Diagnosis

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

MIB: A Mechanistic Interpretability Benchmark

Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation

LLM-SRBench: A New Benchmark for Scientific Equation Discovery with Large Language Models

Toward Total Recall: Enhancing FAIRness through AI-Driven Metadata Standardization

Finding Interest Needle in Popularity Haystack: Improving Retrieval by Modeling Item Exposure

Geometrical Properties of Text Token Embeddings for Strong Semantic Binding in Text-to-Image Generation

sudo rm -rf agentic_security

Imagine to Hear: Auditory Knowledge Generation can be an Effective Assistant for Language Models

Towards Achieving Perfect Multimodal Alignment

nvBench 2.0: Resolving Ambiguity in Text-to-Visualization through Stepwise Reasoning

FedALT: Federated Fine-Tuning through Adaptive Local Training with Rest-of-World LoRA

RONA: Pragmatically Diverse Image Captioning with Coherence Relations

Unifying 2D and 3D Vision-Language Understanding

Revisiting semi-supervised learning in the era of foundation models

AI-based Framework for Robust Model-Based Connector Mating in Robotic Wire Harness Installation

Generalized Interpolating Discrete Diffusion

Towards Autonomous Reinforcement Learning for Real-World Robotic Manipulation with Large Language Models

Straight-Line Diffusion Model for Efficient 3D Molecular Generation

Examining the Mental Health Impact of Misinformation on Social Media Using a Hybrid Transformer-Based Approach

Dynamic spillovers and investment strategies across artificial intelligence ETFs, artificial intelligence tokens, and green markets

Dialogue Without Limits: Constant-Sized KV Caches for Extended Responses in LLMs

LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech Enhancement

from Benign import Toxic: Jailbreaking the Language Model via Adversarial Metaphors

EgoNormia: Benchmarking Physical Social Norm Understanding

PhantomWiki: On-Demand Datasets for Reasoning and Retrieval Evaluation

NeoBERT: A Next-Generation BERT

From Offline to Online Memory-Free and Task-Free Continual Learning via Fine-Grained Hypergradients

AMPO: Active Multi-Preference Optimization for Self-play Preference Selection

SYNTHIA: Novel Concept Design with Affordance Composition

DBudgetKV: Dynamic Budget in KV Cache Compression for Ensuring Optimal Performance

AlphaAgent: LLM-Driven Alpha Mining with Regularized Exploration to Counteract Alpha Decay

DISC: DISC: Dynamic Decomposition Improves LLM Inference Scaling

Predicting Bad Goods Risk Scores with ARIMA Time Series: A Novel Risk Assessment Approach

Space-O-RAN: Enabling Intelligent, Open, and Interoperable Non Terrestrial Networks in 6G

MindLLM: A Subject-Agnostic and Versatile Model for fMRI-to-Text Decoding

Improving the Diffusability of Autoencoders

Tree-of-Debate: Multi-Persona Debate Trees Elicit Critical Thinking for Scientific Comparative Analysis

MMTEB: Massive Multilingual Text Embedding Benchmark

From Sub-Ability Diagnosis to Human-Aligned Generation: Bridging the Gap for Text Length Control via MARKERGEN

How Expressive are Knowledge Graph Foundation Models?

Machine Learning Should Maximize Welfare, but Not by (Only) Maximizing Accuracy

Information Bargaining: Bilateral Commitment in Bayesian Persuasion

Created by

Haebom

저자

Yue Lin, Shuhui Zhu, William A Cunningham, Wenhao Li, Pascal Poupart, Hongyuan Zha, Baoxiang Wang

개요

본 논문은 베이지안 설득이 장기적 상호작용에서 직면하는 계산 복잡성 문제(NP-hardness)를 해결하기 위해 협상 관점을 도입한다. 기존의 베이지안 설득은 단기적 상호작용에서는 효과적이지만, 장기적 상호작용에서는 수신자가 과거 결과와 미래 기대치를 고려한 동적 전략을 채택하기 때문에 계산 복잡성이 발생한다. 논문에서 제시하는 협상 관점은 장기적 설득을 위한 통합적 틀과 공정성 및 파레토 효율성과 같은 바람직한 속성을 지닌 구조화된 해법을 제공한다. 또한, 기존에 혼동되었던 정보적 우위와 선제안자 우위를 명확히 구분한다. 표준 설정에 대한 약간의 수정만으로, 이 관점은 게임 구조에 대한 상식적인 지식을 명시하고 수신자에게 비슷한 수준의 약속 능력을 부여하여 기존의 일방적 설득을 균형 잡힌 정보 협상 프레임워크로 재해석한다. 이 프레임워크는 두 단계의 검증 및 추론 패러다임을 통해 검증되며, 공개적으로 이용 가능한 LLMs인 GPT-3 및 DeepSeek-R1을 사용하여 표준 작업 처리 능력과 설득 시나리오에서의 결과가 정보 협상 프레임워크의 제안과 일치하는지 테스트한다. 모든 코드, 결과 및 터미널 로그가 공개적으로 제공된다.

시사점, 한계점

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시사점:

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베이지안 설득의 장기적 상호작용에서의 계산 복잡성 문제 해결을 위한 새로운 협상 관점 제시

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장기적 설득을 위한 통합적이고 구조화된 해법 제공 (공정성, 파레토 효율성)

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정보적 우위와 선제안자 우위의 명확한 구분

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일방적 설득을 균형 잡힌 정보 협상 프레임워크로 재해석

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LLMs를 활용한 프레임워크 검증 및 실험 결과 공개

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한계점:

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제시된 협상 프레임워크의 일반화 가능성 및 실제 세계 적용 가능성에 대한 추가 연구 필요

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사용된 LLMs의 한계가 결과에 미칠 수 있는 영향에 대한 고찰 필요

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더욱 복잡한 상호작용이나 다양한 유형의 설득 시나리오에 대한 적용성 검토 필요

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