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.

When Generative AI Meets Extended Reality: Enabling Scalable and Natural Interactions

An Explainable Market Integrity Monitoring System with Multi-Source Attention Signals and Transparent Scoring

Can We Trust LLM Detectors?

Embedding Retrofitting: Data Engineering for better RAG

Entropy-Tree: Tree-Based Decoding with Entropy-Guided Exploration

Elsewise: Authoring AI-Based Interactive Narrative with Possibility Space Visualization

Agentic Persona Control and Task State Tracking for Realistic User Simulation in Interactive Scenarios

LLM-based Multimodal Feedback Produces Equivalent Learning and Better Student Perceptions than Educator Feedback

Psychometric Comparability of LLM-Based Digital Twins

Scalable Board Expansion within a General Game System

Structured Hints for Sample-Efficient Lean Theorem Proving

Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

LLM Prompt Evaluation for Educational Applications

Multimodal Climate Disinformation Detection: Integrating Vision-Language Models with External Knowledge Sources

Controlling Long-Horizon Behavior in Language Model Agents with Explicit State Dynamics

Designing faster mixed integer linear programming algorithm via learning the optimal path

AgriPINN: A Process-Informed Neural Network for Interpretable and Scalable Crop Biomass Prediction Under Water Stress

Grounding Large Language Models in Reaction Knowledge Graphs for Synthesis Retrieval

Deja Vu in Plots: Leveraging Cross-Session Evidence with Retrieval-Augmented LLMs for Live Streaming Risk Assessment

Decoupling Return-to-Go for Efficient Decision Transformer

Natural Language-Driven Global Mapping of Martian Landforms

ICON: Invariant Counterfactual Optimization with Neuro-Symbolic Priors for Text-Based Person Search

EvoCUA: Evolving Computer Use Agents via Learning from Scalable Synthetic Experience

ErrorMap and ErrorAtlas: Charting the Failure Landscape of Large Language Models

Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided Verification

VitalDiagnosis: AI-Driven Ecosystem for 24/7 Vital Monitoring and Chronic Disease Management

Creativity in the Age of AI: Rethinking the Role of Intentional Agency

Agentic Confidence Calibration

Off-Policy Actor-Critic with Sigmoid-Bounded Entropy for Real-World Robot Learning

Tabular Incremental Inference

PhysProver: Advancing Automatic Theorem Proving for Physics

Benchmarking Text-to-Python against Text-to-SQL: The Impact of Explicit Logic and Ambiguity

Investigation of the Generalisation Ability of Genetic Programming-evolved Scheduling Rules in Dynamic Flexible Job Shop Scheduling

AgentSM: Semantic Memory for Agentic Text-to-SQL

Improving Methodologies for LLM Evaluations Across Global Languages

Agentic Uncertainty Quantification

From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models

Improving Methodologies for Agentic Evaluations Across Domains: Leakage of Sensitive Information, Fraud and Cybersecurity Threats

Predictive Coding and Information Bottleneck for Hallucination Detection in Large Language Models

Agentic AI Governance and Lifecycle Management in Healthcare

CogToM: A Comprehensive Theory of Mind Benchmark inspired by Human Cognition for Large Language Models

Autonomous Business System via Neuro-symbolic AI

ALIGNAgent: Adaptive Learner Intelligence for Gap Identification and Next-step guidance

From Generative Engines to Actionable Simulators: The Imperative of Physical Grounding in World Models

TransportAgents: a multi-agents LLM framework for traffic accident severity prediction

The Dark Side of AI Transformers: Sentiment Polarization & the Loss of Business Neutrality by NLP Transformers

Tracking the Limits of Knowledge Propagation: How LLMs Fail at Multi-Step Reasoning with Conflicting Knowledge

MiRAGE: A Multiagent Framework for Generating Multimodal Multihop Question-Answer Dataset for RAG Evaluation

Reliability by design: quantifying and eliminating fabrication risk in LLMs. From generative to consultative AI: a comparative analysis in the legal domain and lessons for high-stakes knowledge bases

A tensor network formalism for neuro-symbolic AI

Not Your Typical Sycophant: The Elusive Nature of Sycophancy in Large Language Models

Beyond Prompting: Efficient and Robust Contextual Biasing for Speech LLMs via Logit-Space Integration (LOGIC)

GeMM-GAN: A Multimodal Generative Model Conditioned on Histopathology Images and Clinical Descriptions for Gene Expression Profile Generation

Logic Programming on Knowledge Graph Networks And its Application in Medical Domain

Prometheus Mind: Retrofitting Memory to Frozen Language Models

Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents

The Paradigm Shift: A Comprehensive Survey on Large Vision Language Models for Multimodal Fake News Detection

Aeon: High-Performance Neuro-Symbolic Memory Management for Long-Horizon LLM Agents

DeepSurvey-Bench: Evaluating Academic Value of Automatically Generated Scientific Survey

Uncovering Latent Bias in LLM-Based Emergency Department Triage Through Proxy Variables

Gated Sparse Attention: Combining Computational Efficiency with Training Stability for Long-Context Language Models

AI/ML in 3GPP 5G Advanced -- Services and Architecture

CookAnything: A Framework for Flexible and Consistent Multi-Step Recipe Image Generation

Dynamic Correction of Erroneous State Estimates via Diffusion Bayesian Exploration

Concept-Guided Backdoor Attack on Vision Language Models

On the Holographic Geometry of Deterministic Computation

Decoding inner speech with an end-to-end brain-to-text neural interface

Physics-informed Neural Operator Learning for Nonlinear Grad-Shafranov Equation

MindEval: Benchmarking Language Models on Multi-turn Mental Health Support

LAET: A Layer-wise Adaptive Ensemble Tuning Framework for Pretrained Language Models

FAST-CAD: A Fairness-Aware Framework for Non-Contact Stroke Diagnosis

Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationale

SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control

MOSS: Efficient and Accurate FP8 LLM Training with Microscaling and Automatic Scaling

Data-Augmented Deep Learning for Downhole Depth Sensing and Field Validation

Chinese Discharge Drug Recommendation in Metabolic Diseases with Large Language Models

Analysing Moral Bias in Finetuned LLMs through Mechanistic Interpretability

Orders in Chaos: Enhancing Large-Scale MoE LLM Serving with Data Movement Forecasting

Reinforce-Ada: An Adaptive Sampling Framework under Non-linear RL Objectives

TempoControl: Temporal Attention Guidance for Text-to-Video Models

AortaDiff: A Unified Multitask Diffusion Framework For Contrast-Free AAA Imaging

SoREX: Towards Self-Explainable Social Recommendation with Relevant Ego-Path Extraction

The AI Productivity Index (APEX)

Uncovering Grounding IDs: How External Cues Shape Multimodal Binding

Pushing Toward the Simplex Vertices: A Simple Remedy for Code Collapse in Smoothed Vector Quantization

V-CECE: Visual Counterfactual Explanations via Conceptual Edits

Momentum-constrained Hybrid Heuristic Trajectory Optimization Framework with Residual-enhanced DRL for Visually Impaired Scenarios

HARP: Hallucination Detection via Reasoning Subspace Projection

Rethinking Sparse Autoencoders: Select-and-Project for Fairness and Control from Encoder Features Alone

IPA: An Information-Reconstructive Input Projection Framework for Efficient Foundation Model Adaptation

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders

ORFuzz: Fuzzing the "Other Side" of LLM Safety -- Testing Over-Refusal

Retro-Expert: Collaborative Reasoning for Interpretable Retrosynthesis

A Survey on Diffusion Language Models

CodeNER: Code Prompting for Named Entity Recognition

ReSem3D: Refinable 3D Spatial Constraints via Fine-Grained Semantic Grounding for Generalizable Robotic Manipulation

VERIRAG: A Post-Retrieval Auditing of Scientific Study Summaries

SustainDiffusion: Optimising the Social and Environmental Sustainability of Stable Diffusion Models

LittleBit: Ultra Low-Bit Quantization via Latent Factorization

Real-Time Execution of Action Chunking Flow Policies

AlignBot: Aligning VLM-powered Customized Task Planning with User Reminders Through Fine-Tuning for Household Robots

Created by

Haebom

Category

Empty

저자

Zhaxizhuoma Zhaxizhuoma, Pengan Chen, Ziniu Wu, Jiawei Sun, Dong Wang, Peng Zhou, Nieqing Cao, Yan Ding, Bin Zhao, Xuelong Li

개요

AlignBot은 가정용 로봇을 위한 VLM 기반 맞춤형 작업 계획을 사용자의 알림과 효과적으로 정렬하도록 설계된 새로운 프레임워크입니다. 제한적이고 다양하며 다중 모달인 가정 환경의 사용자 알림의 특성을 고려하여, AlignBot은 GPT-4o를 위한 어댑터 역할을 하는 미세 조정된 LLaVA-7B 모델을 사용합니다. 이 어댑터 모델은 개인화된 선호도, 수정 지침, 상황별 지원과 같은 다양한 형태의 사용자 알림을 구조화된 지침 형식의 큐로 변환하여 GPT-4o가 맞춤형 작업 계획을 생성하도록 유도합니다. 또한 AlignBot은 GPT-4o에 대한 프롬프트로 작업 관련 과거 성공 사례를 선택하는 동적 검색 메커니즘을 통합하여 작업 계획 정확도를 더욱 향상시킵니다. 실제 가정 환경을 모방하여 실험실에서 구축된 실제 가정 환경에서 실험을 수행하여 AlignBot의 효과를 검증했습니다. 자원봉사자의 알림에서 파생된 1,500개 이상의 항목으로 구성된 다중 모달 데이터 세트를 훈련 및 평가에 사용했습니다. 결과는 AlignBot이 사용자 알림을 해석하고 정렬하여 기존의 LLM 및 VLM 기반 플래너보다 맞춤형 작업 계획을 크게 개선하며, 21.6%인 일반 GPT-4o 기준선에 비해 86.8%의 성공률을 달성하여 65% 향상 및 4배 이상의 효율성을 보여줍니다. 보충 자료는 https://yding25.com/AlignBot/ 에서 확인할 수 있습니다.

AlignBot: Aligning VLM-powered Customized Task Planning with User Feedback Through Fine-Tuning for Household Robots

시사점, 한계점

•

시사점:

◦

사용자 알림을 효과적으로 통합하여 가정용 로봇의 맞춤형 작업 계획 정확도를 크게 향상시켰습니다. (65% 향상, 성공률 86.8%)

◦

LLaVA-7B와 GPT-4o의 조합을 통해 다양한 형태의 다중 모달 알림을 효과적으로 처리하는 새로운 프레임워크를 제시했습니다.

◦

실제 가정 환경을 모방한 실험을 통해 AlignBot의 실용성과 효과를 검증했습니다.

•

한계점:

◦

실험 환경이 실제 가정 환경과 완벽하게 일치하지 않을 수 있습니다. (실험실 환경에서의 실험)

◦

사용된 데이터셋의 규모(1,500개 항목)가 더 큰 규모의 데이터셋에 비해 제한적일 수 있습니다.

◦

특정 알림 유형이나 상황에 대한 일반화 성능에 대한 추가적인 연구가 필요할 수 있습니다.

◦

GPT-4o 사용에 따른 비용 및 접근성 문제가 존재할 수 있습니다.

Made with Slashpage