Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

Inductive Moment Matching

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Ideas in Inference-time Scaling can Benefit Generative Pre-training Algorithms

FaceID-6M: A Large-Scale, Open-Source FaceID Customization Dataset

Interactive Medical Image Analysis with Concept-based Similarity Reasoning

Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

LightMotion: A Light and Tuning-free Method for Simulating Camera Motion in Video Generation

A Transformer Model for Predicting Chemical Reaction Products from Generic Templates

CBW: Towards Dataset Ownership Verification for Speaker Verification via Clustering-based Backdoor Watermarking

The Lazy Student's Dream: ChatGPT Passing an Engineering Course on Its Own

VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control

Multi-Task Reinforcement Learning Enables Parameter Scaling

Balcony: A Lightweight Approach to Dynamic Inference of Generative Language Models

Prediction of Frozen Region Growth in Kidney Cryoablation Intervention Using a 3D Flow-Matching Model

Call for Rigor in Reporting Quality of Instruction Tuning Data

KunlunBaize: LLM with Multi-Scale Convolution and Multi-Token Prediction Under TransformerX Framework

(How) Do Language Models Track State?

IterPref: Focal Preference Learning for Code Generation via Iterative Debugging

PaCA: Partial Connection Adaptation for Efficient Fine-Tuning

Forgotten Polygons: Multimodal Large Language Models are Shape-Blind

Q-PETR: Quant-aware Position Embedding Transformation for Multi-View 3D Object Detection

FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling

Helix-mRNA: A Hybrid Foundation Model For Full Sequence mRNA Therapeutics

IMLE Policy: Fast and Sample Efficient Visuomotor Policy Learning via Implicit Maximum Likelihood Estimation

Reasoning-Augmented Conversation for Multi-Turn Jailbreak Attacks on Large Language Models

Equivariant Masked Position Prediction for Efficient Molecular Representation

IRepair: An Intent-Aware Approach to Repair Data-Driven Errors in Large Language Models

Automated Consistency Analysis of LLMs

ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates

Rationalization Models for Text-to-SQL

Reflection-Window Decoding: Text Generation with Selective Refinement

Agentic Bug Reproduction for Effective Automated Program Repair at Google

Data Duplication: A Novel Multi-Purpose Attack Paradigm in Machine Unlearning

MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods

KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks

TexAVi: Generating Stereoscopic VR Video Clips from Text Descriptions

Multi-P$^2$A: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models

Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training

SweetTok: Semantic-Aware Spatial-Temporal Tokenizer for Compact Video Discretization

DMin: Scalable Training Data Influence Estimation for Diffusion Models

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents

LayoutVLM: Differentiable Optimization of 3D Layout via Vision-Language Models

RL-MILP Solver: A Reinforcement Learning Approach for Solving Mixed-Integer Linear Programs with Graph Neural Networks

Proto Successor Measure: Representing the Behavior Space of an RL Agent

KinMo: Kinematic-aware Human Motion Understanding and Generation

Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks

OminiControl: Minimal and Universal Control for Diffusion Transformer

MTA: Multimodal Task Alignment for BEV Perception and Captioning

PyGen: A Collaborative Human-AI Approach to Python Package Creation

Fair Summarization: Bridging Quality and Diversity in Extractive Summaries

AtlasSeg: Atlas Prior Guided Dual-U-Net for Cortical Segmentation in Fetal Brain MRI

V-LoRA: An Efficient and Flexible System Boosts Vision Applications with LoRA LMM

Fourier Head: Helping Large Language Models Learn Complex Probability Distributions

Conditional diffusions for neural posterior estimation

LLM-HDR: Bridging LLM-based Perception and Self-Supervision for Unpaired LDR-to-HDR Image Reconstruction

Chemistry-Inspired Diffusion with Non-Differentiable Guidance

Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion

6DGS: Enhanced Direction-Aware Gaussian Splatting for Volumetric Rendering

CAX: Cellular Automata Accelerated in JAX

Emotion-Aware Embedding Fusion in LLMs (Flan-T5, LLAMA 2, DeepSeek-R1, and ChatGPT 4) for Intelligent Response Generation

What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach

Meta-RTL: Reinforcement-Based Meta-Transfer Learning for Low-Resource Commonsense Reasoning

LEMMo-Plan: LLM-Enhanced Learning from Multi-Modal Demonstration for Planning Sequential Contact-Rich Manipulation Tasks

Training with Differential Privacy: A Gradient-Preserving Noise Reduction Approach with Provable Security

ASMA: An Adaptive Safety Margin Algorithm for Vision-Language Drone Navigation via Scene-Aware Control Barrier Functions

Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Inference-Time Selective Debiasing to Enhance Fairness in Text Classification Models

Detect, Investigate, Judge and Determine: A Knowledge-guided Framework for Few-shot Fake News Detection

How Data Inter-connectivity Shapes LLMs Unlearning: A Structural Unlearning Perspective

Value Improved Actor Critic Algorithms

Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search

Curriculum Direct Preference Optimization for Diffusion and Consistency Models

Is the House Ready For Sleeptime? Generating and Evaluating Situational Queries for Embodied Question Answering

RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion

Adversarial Guided Diffusion Models for Adversarial Purification

M-HOF-Opt: Multi-Objective Hierarchical Output Feedback Optimization via Multiplier Induced Loss Landscape Scheduling

The VampPrior Mixture Model

Regularization by Texts for Latent Diffusion Inverse Solvers

Deep Tensor Network

Identifying the Truth of Global Model: A Generic Solution to Defend Against Byzantine and Backdoor Attacks in Federated Learning (full version)

Generalizable Imitation Learning Through Pre-Trained Representations

Hypergraph Structure Inference From Data Under Smoothness Prior

HowkGPT: Investigating the Detection of ChatGPT-generated University Student Homework through Context-Aware Perplexity Analysis

SketchOGD: Memory-Efficient Continual Learning

ChatGPT-4 in the Turing Test: A Critical Analysis

Toward an Evaluation Science for Generative AI Systems

WritingBench: A Comprehensive Benchmark for Generative Writing

ToolFuzz -- Automated Agent Tool Testing

Building Interval Type-2 Fuzzy Membership Function: A Deck of Cards based Co-constructive Approach

Optimus-2: Multimodal Minecraft Agent with Goal-Observation-Action Conditioned Policy

Learning to Plan with Personalized Preferences

Exponential Speedups by Rerooting Levin Tree Search

A Unified Framework for Motion Reasoning and Generation in Human Interaction

Agent-Oriented Planning in Multi-Agent Systems

Dynamic Analysis and Adaptive Discriminator for Fake News Detection

A Practical Review of Mechanistic Interpretability for Transformer-Based Language Models

AI Data Readiness Inspector (AIDRIN) for Quantitative Assessment of Data Readiness for AI

Nondeterministic Causal Models

X-SHIELD: Regularization for eXplainable Artificial Intelligence

Categorical semantics of compositional reinforcement learning

LEMMo-Plan: LLM-Enhanced Learning from Multi-Modal Demonstration for Planning Sequential Contact-Rich Manipulation Tasks

Created by

Haebom

저자

Kejia Chen, Zheng Shen, Yue Zhang, Lingyun Chen, Fan Wu, Zhenshan Bing, Sami Haddadin, Alois Knoll

개요

본 논문은 장기간 조작 작업의 작업 계획에 있어 대규모 언어 모델(LLM)의 인기를 고려하여, LLM이 생성한 계획의 유효성을 높이기 위해 시각적 데모와 온라인 비디오를 활용하는 기존 방식의 한계를 지적합니다. 미세한 움직임과 풍부한 접촉 상호작용이 필요한 조작 작업에서는 시각적 인식만으로는 LLM이 데모를 완전히 해석하기에 부족하며, 힘 관련 매개변수와 조건에 대한 정보가 제한적이라는 점을 문제점으로 제시합니다. 따라서 본 논문에서는 인간 데모의 촉각 및 힘-토크 정보를 통합하여 LLM의 새로운 작업 시나리오 계획 능력을 향상시키는 컨텍스트 학습 프레임워크를 제안합니다. 각 모달리티를 순차적으로 통합하는 부트스트랩 추론 파이프라인을 통해 포괄적인 작업 계획을 생성하고, 이를 새로운 작업 구성의 계획 참조로 사용하는 방법을 제시합니다. 두 가지 서로 다른 순차적 조작 작업에 대한 실제 실험을 통해 제안된 프레임워크의 효과를 검증합니다.

시사점, 한계점

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시사점:

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촉각 및 힘-토크 정보를 활용하여 LLM의 작업 계획 성능 향상 가능성을 보여줌.

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다중 모달리티 데모를 효과적으로 활용하는 부트스트랩 추론 파이프라인 제시.

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실제 로봇 환경에서의 실험을 통해 프레임워크의 실효성 검증.

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한계점:

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제안된 프레임워크의 일반성 및 다양한 작업 유형에 대한 적용성 추가 연구 필요.

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데이터 수집 및 전처리 과정의 복잡성 및 효율성 개선 필요.

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다양한 센서 데이터 통합 및 노이즈 처리에 대한 추가적인 연구 필요.

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