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.

Teaching the Teacher: Improving Neural Network Distillability for Symbolic Regression via Jacobian Regularization

Bayesian Optimization of Process Parameters of a Sensor-Based Sorting System using Gaussian Processes as Surrogate Models

Multi-modal Relational Item Representation Learning for Inferring Substitutable and Complementary Items

SourceSplice: Source Selection for Machine Learning Tasks

OneShield -- the Next Generation of LLM Guardrails

RecPS: Privacy Risk Scoring for Recommender Systems

HuiduRep: A Robust Self-Supervised Framework for Learning Neural Representations from Extracellular Recordings

Leveraging Synthetic Data for Question Answering with Multilingual LLMs in the Agricultural Domain

Time-RA: Towards Time Series Reasoning for Anomaly with LLM Feedback

A Segmented Robot Grasping Perception Neural Network for Edge AI

Binarizing Physics-Inspired GNNs for Combinatorial Optimization

Disentangling Neural Disjunctive Normal Form Models

The Second Machine Turn: From Checking Proofs to Creating Concepts

EmissionNet: Air Quality Pollution Forecasting for Agriculture

Emergent Semantics Beyond Token Embeddings: Transformer LMs with Frozen Visual Unicode Representations

Evaluating LLMs on Real-World Forecasting Against Human Superforecasters

Sign Spotting Disambiguation using Large Language Models

RAG-R1 : Incentivize the Search and Reasoning Capabilities of LLMs through Multi-query Parallelism

Discovering the underlying analytic structure within Standard Model constants using artificial intelligence

MR-CLIP: Efficient Metadata-Guided Learning of MRI Contrast Representations

Curious Causality-Seeking Agents Learn Meta Causal World

Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models

Private GPTs for LLM-driven testing in software development and machine learning

DINO-R1: Incentivizing Reasoning Capability in Vision Foundation Models

AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corpora

Mitigating Gender Bias via Fostering Exploratory Thinking in LLMs

HumaniBench: A Human-Centric Framework for Large Multimodal Models Evaluation

Are Sparse Autoencoders Useful for Java Function Bug Detection?

Credible Plan-Driven RAG Method for Multi-Hop Question Answering

Debunking with Dialogue? Exploring AI-Generated Counterspeech to Challenge Conspiracy Theories

E2E Parking Dataset: An Open Benchmark for End-to-End Autonomous Parking

Dominated Actions in Imperfect-Information Games

FakeIDet: Exploring Patches for Privacy-Preserving Fake ID Detection

Simultaneous Motion And Noise Estimation with Event Cameras

Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation

Novice Developers' Perspectives on Adopting LLMs for Software Development: A Systematic Literature Review

ULTHO: Ultra-Lightweight yet Efficient Hyperparameter Optimization in Deep Reinforcement Learning

A Survey on Post-training of Large Language Models

Do Large Language Models Know How Much They Know?

Better Embeddings with Coupled Adam

Semantic-Aware Adaptive Video Streaming Using Latent Diffusion Models for Wireless Networks

An Investigation into Value Misalignment in LLM-Generated Texts for Cultural Heritage

Embracing Large Language Models in Traffic Flow Forecasting

A Large Sensor Foundation Model Pretrained on Continuous Glucose Monitor Data for Diabetes Management

FLOAT: Generative Motion Latent Flow Matching for Audio-driven Talking Portrait

Un-mixing Test-time Adaptation under Heterogeneous Data Streams

PATH: A Discrete-sequence Dataset for Evaluating Online Unsupervised Anomaly Detection Approaches for Multivariate Time Series

Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics

Cobblestone: Iterative Automation for Formal Verification

Cooperative and Asynchronous Transformer-based Mission Planning for Heterogeneous Teams of Mobile Robots

Policy Maps: Tools for Guiding the Unbounded Space of LLM Behaviors

AttnMod: Attention-Based New Art Styles

Loss Landscape Degeneracy and Stagewise Development in Transformers

Tackling Size Generalization of Graph Neural Networks on Biological Data from a Spectral Perspective

Gradient Leakage Defense with Key-Lock Module for Federated Learning

Seed-Prover: Deep and Broad Reasoning for Automated Theorem Proving

Semantic Chain-of-Trust: Autonomous Trust Orchestration for Collaborator Selection via Hypergraph-Aided Agentic AI

How Far Are AI Scientists from Changing the World?

A Survey of Self-Evolving Agents: On Path to Artificial Super Intelligence

E.A.R.T.H.: Structuring Creative Evolution through Model Error in Generative AI

On Gradual Semantics for Assumption-Based Argumentation

Sound and Complete Neurosymbolic Reasoning with LLM-Grounded Interpretations

Dynamic Knowledge Exchange and Dual-diversity Review: Concisely Unleashing the Potential of a Multi-Agent Research Team

ORFS-agent: Tool-Using Agents for Chip Design Optimization

World Model-Based Learning for Long-Term Age of Information Minimization in Vehicular Networks

The Urban Impact of AI: Modeling Feedback Loops in Next-Venue Recommendation

BOOST: Bootstrapping Strategy-Driven Reasoning Programs for Program-Guided Fact-Checking

OR-LLM-Agent: Automating Modeling and Solving of Operations Research Optimization Problems with Reasoning LLM

Causal Explanations for Image Classifiers

BCR-DRL: Behavior- and Context-aware Reward for Deep Reinforcement Learning in Human-AI Coordination

Federated Cross-Training Learners for Robust Generalization under Data Heterogeneity

Identifying Unique Spatial-Temporal Bayesian Network without Markov Equivalence

Do They Understand Them? An Updated Evaluation on Nonbinary Pronoun Handling in Large Language Models

SpA2V: Harnessing Spatial Auditory Cues for Audio-driven Spatially-aware Video Generation

Sample-Aware Test-Time Adaptation for Medical Image-to-Image Translation

MMBERT: Scaled Mixture-of-Experts Multimodal BERT for Robust Chinese Hate Speech Detection under Cloaking Perturbations

A Simple and Effective Method for Uncertainty Quantification and OOD Detection

Harnessing the Power of Interleaving and Counterfactual Evaluation for Airbnb Search Ranking

Is It Really You? Exploring Biometric Verification Scenarios in Photorealistic Talking-Head Avatar Videos

Agentic large language models improve retrieval-based radiology question answering

Out-of-Context Abduction: LLMs Make Inferences About Procedural Data Leveraging Declarative Facts in Earlier Training Data

How LLMs are Shaping the Future of Virtual Reality

Adaptive Machine Learning-Driven Multi-Fidelity Stratified Sampling for Failure Analysis of Nonlinear Stochastic Systems

Dynamically Adaptive Reasoning via LLM-Guided MCTS for Efficient and Context-Aware KGQA

Nested Graph Pseudo-Label Refinement for Noisy Label Domain Adaptation Learning

JSON-Bag: A generic game trajectory representation

NyayaRAG: Realistic Legal Judgment Prediction with RAG under the Indian Common Law System

Efficient Solution and Learning of Robust Factored MDPs

D3: Training-Free AI-Generated Video Detection Using Second-Order Features

On-Device Diffusion Transformer Policy for Efficient Robot Manipulation

Segment First, Retrieve Better: Realistic Legal Search via Rhetorical Role-Based Queries

Medical Reasoning in the Era of LLMs: A Systematic Review of Enhancement Techniques and Applications

Advancing Quantum Information Science Pre-College Education: The Case for Learning Sciences Collaboration

Backdoor Attacks on Deep Learning Face Detection

Similarity-Based Self-Construct Graph Model for Predicting Patient Criticalness Using Graph Neural Networks and EHR Data

Prompting Science Report 3: I'll pay you or I'll kill you -- but will you care?

Composable OS Kernel Architectures for Autonomous Intelligence

LeakSealer: A Semisupervised Defense for LLMs Against Prompt Injection and Leakage Attacks

Wukong Framework for Not Safe For Work Detection in Text-to-Image systems

OmniUnet: A Multimodal Network for Unstructured Terrain Segmentation on Planetary Rovers Using RGB, Depth, and Thermal Imagery

Video-MMLU: A Massive Multi-Discipline Lecture Understanding Benchmark

작성자

Haebom

저자

Enxin Song, Wenhao Chai, Weili Xu, Jianwen Xie, Yuxuan Liu, Gaoang Wang

개요

본 논문은 다양한 학문 분야의 강의를 이해하는 능력을 평가하기 위한 대규모 벤치마크인 Video-MMLU를 소개합니다. 0.5B에서 40B 파라미터에 이르는 90개 이상의 오픈소스 및 독점 모델을 평가하여, 현재 모델들이 강의 이해에 필요한 인지적 과제, 특히 지각과 추론을 모두 필요로 하는 작업에서 한계를 가지고 있음을 보여줍니다. 또한, 시각 토큰 수와 대규모 언어 모델이 성능에 미치는 영향을 분석하여 다중 모드 지각과 추론의 상호 작용에 대한 통찰력을 제공합니다.

시사점, 한계점

•

시사점: 다중 학문 분야 강의 이해에 대한 새로운 벤치마크인 Video-MMLU를 제시하여 LMM의 성능을 종합적으로 평가할 수 있는 기반을 마련했습니다. 시각 정보와 언어 정보의 상호작용에 대한 이해를 높일 수 있는 실험 결과를 제공했습니다.

•

한계점: 현재 LMM들이 다중 학문 강의 이해에 필요한 지각 및 추론 능력에서 여전히 한계를 가지고 있음을 보여줍니다. Video-MMLU 벤치마크 자체의 한계 및 개선점에 대한 논의가 부족할 수 있습니다. 특정 모델이나 매개변수 크기에 편향된 결과 해석 가능성이 존재합니다.

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