haebom
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.
A Theoretical Framework for Environmental Similarity and Vessel Mobility as Coupled Predictors of Marine Invasive Species Pathways
CareMedEval dataset: Evaluating Critical Appraisal and Reasoning in the Biomedical Field
Node-Based Editing for Multimodal Generation of Text, Audio, Image, and Video
Control Barrier Function for Aligning Large Language Models
A Criminology of Machines
FATE: A Formal Benchmark Series for Frontier Algebra of Multiple Difficulty Levels
PoCo: Agentic Proof-of-Concept Exploit Generation for Smart Contracts
Causal Graph Neural Networks for Healthcare
LA-MARRVEL: A Knowledge-Grounded and Language-Aware LLM Reranker for AI-MARRVEL in Rare Disease Diagnosis
OceanAI: A Conversational Platform for Accurate, Transparent, Near-Real-Time Oceanographic Insights
Pay for The Second-Best Service: A Game-Theoretic Approach Against Dishonest LLM Providers
Artificial Intelligence in Elementary STEM Education: A Systematic Review of Current Applications and Future Challenges
Non-Convex Over-the-Air Heterogeneous Federated Learning: A Bias-Variance Trade-off
TraceTrans: Translation and Spatial Tracing for Surgical Prediction
TowerVision: Understanding and Improving Multilinguality in Vision-Language Models
Gestura: A LVLM-Powered System Bridging Motion and Semantics for Real-Time Free-Form Gesture Understanding
ADPO: Anchored Direct Preference Optimization
Rewarding the Journey, Not Just the Destination: A Composite Path and Answer Self-Scoring Reward Mechanism for Test-Time Reinforcement Learning
RealDPO: Real or Not Real, that is the Preference
Deep Edge Filter: Return of the Human-Crafted Layer in Deep Learning
Mathematics with large language models as provers and verifiers
Integrating Sequential and Relational Modeling for User Events: Datasets and Prediction Tasks
A Systematic Evaluation of Self-Supervised Learning for Label-Efficient Sleep Staging with Wearable EEG
Learning to Navigate Socially Through Proactive Risk Perception
Training Large Language Models To Reason In Parallel With Global Forking Tokens
ChessArena: A Chess Testbed for Evaluating Strategic Reasoning Capabilities of Large Language Models
HyperAdapt: Simple High-Rank Adaptation
Comparing Computational Pathology Foundation Models using Representational Similarity Analysis
Back to Ear: Perceptually Driven High Fidelity Music Reconstruction
Test-Time Warmup for Multimodal Large Language Models
Zero-Shot Referring Expression Comprehension via Vison-Language True/False Verification
Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications
Balancing Quality and Variation: Spam Filtering Distorts Data Label Distributions
A Multi-target Bayesian Transformer Framework for Predicting Cardiovascular Disease Biomarkers during Pandemics
Med-GLIP: Advancing Medical Language-Image Pre-training with Large-scale Grounded Dataset
NyayaRAG: Realistic Legal Judgment Prediction with RAG under the Indian Common Law System
XRoboToolkit: A Cross-Platform Framework for Robot Teleoperation
Vibe Coding as a Reconfiguration of Intent Mediation in Software Development: Definition, Implications, and Research Agenda
GENIAL: Generative Design Space Exploration via Network Inversion for Low Power Algorithmic Logic Units
MeAJOR Corpus: A Multi-Source Dataset for Phishing Email Detection
Deep Graph Learning for Industrial Carbon Emission Analysis and Policy Impact
Towards Efficient and Accurate Spiking Neural Networks via Adaptive Bit Allocation
Advanced Sign Language Video Generation with Compressed and Quantized Multi-Condition Tokenization
HoliSafe: Holistic Safety Benchmarking and Modeling for Vision-Language Model
Explicit Density Approximation for Neural Implicit Samplers Using a Bernstein-Based Convex Divergence
HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts
Reasoning Models Hallucinate More: Factuality-Aware Reinforcement Learning for Large Reasoning Models
Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data
Hierarchical Retrieval with Evidence Curation for Open-Domain Financial Question Answering on Standardized Documents
Two Causally Related Needles in a Video Haystack
Robustness in Large Language Models: A Survey of Mitigation Strategies and Evaluation Metrics
Autocomp: A Powerful and Portable Code Optimizer for Tensor Accelerators
But what is your honest answer? Aiding LLM-judges with honest alternatives using steering vectors
Learning Dynamics of RNNs in Closed-Loop Environments
Revisiting Residual Connections: Orthogonal Updates for Stable and Efficient Deep Networks
Multimodal Cancer Modeling in the Age of Foundation Model Embeddings
Benchmarking LLM Faithfulness in RAG with Evolving Leaderboards
TathyaNyaya and FactLegalLlama: Advancing Factual Judgment Prediction and Explanation in the Indian Legal Context
Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models
Efficient Model Development through Fine-tuning Transfer
SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning
Pragmatic Reasoning improves LLM Code Generation
KGGen: Extracting Knowledge Graphs from Plain Text with Language Models
How Memory in Optimization Algorithms Implicitly Modifies the Loss
GASP: Efficient Black-Box Generation of Adversarial Suffixes for Jailbreaking LLMs
Transferable & Stealthy Ensemble Attacks: A Black-Box Jailbreaking Framework for Large Language Models
Understanding Adam Requires Better Rotation Dependent Assumptions
Beyond the Kolmogorov Barrier: A Learnable Weighted Hybrid Autoencoder for Model Order Reduction
Residual Kolmogorov-Arnold Network for Enhanced Deep Learning
Legal Fact Prediction: The Missing Piece in Legal Judgment Prediction
LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users
Projection Methods for Operator Learning and Universal Approximation
Stochastic Diffusion: A Diffusion Probabilistic Model for Stochastic Time Series Forecasting
A Unified Kernel for Neural Network Learning
Toward Autonomous Engineering Design: A Knowledge-Guided Multi-Agent Framework
SnapStream: Efficient Long Sequence Decoding on Dataflow Accelerators
Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning
BOTS: A Unified Framework for Bayesian Online Task Selection in LLM Reinforcement Finetuning
Toward Clinically Grounded Foundation Models in Pathology
Seg the HAB: Language-Guided Geospatial Algae Bloom Reasoning and Segmentation
A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning
Structured Debate Improves Corporate Credit Reasoning in Financial AI
Cross-modal Causal Intervention for Alzheimer's Disease Prediction
Evaluating LLM-Contaminated Crowdsourcing Data Without Ground Truth
Style2Code: A Style-Controllable Code Generation Framework with Dual-Modal Contrastive Representation Learning
Building Altruistic and Moral AI Agent with Brain-inspired Emotional Empathy Mechanisms
"Let's Agree to Disagree": Investigating the Disagreement Problem in Explainable AI for Text Summarization
Collaboration Dynamics and Reliability Challenges of Multi-Agent LLM Systems in Finite Element Analysis
Discussion Graph Semantics of First-Order Logic with Equality for Reasoning about Discussion and Argumentation
X-Diffusion: Training Diffusion Policies on Cross-Embodiment Human Demonstrations
Addressing divergent representations from causal interventions on neural networks
Integrating Temporal and Structural Context in Graph Transformers for Relational Deep Learning
LLM-as-a-Judge: Toward World Models for Slate Recommendation Systems
Are language models aware of the road not taken? Token-level uncertainty and hidden state dynamics
Alternative Fairness and Accuracy Optimization in Criminal Justice
RAGalyst: Automated Human-Aligned Agentic Evaluation for Domain-Specific RAG
Decoding Emergent Big Five Traits in Large Language Models: Temperature-Dependent Expression and Architectural Clustering
OUNLP at TSAR 2025 Shared Task: Multi-Round Text Simplifier via Code Generation
RUST-BENCH: Benchmarking LLM Reasoning on Unstructured Text within Structured Tables
Q3R: Quadratic Reweighted Rank Regularizer for Effective Low-Rank Training
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MLLM as a UI Judge: Benchmarking Multimodal LLMs for Predicting Human Perception of User Interfaces
Created by
Haebom
저자
Reuben A. Luera, Ryan Rossi, Franck Dernoncourt, Samyadeep Basu, Sungchul Kim, Subhojyoti Mukherjee, Puneet Mathur, Ruiyi Zhang, Jihyung Kil, Nedim Lipka, Seunghyun Yoon, Jiuxiang Gu, Zichao Wang, Cindy Xiong Bearfield, Branislav Kveton
개요
본 논문은 사용자 인터페이스(UI) 디자인 과정에서 다중 모드 대규모 언어 모델(MLLMs)이 초기 평가자 역할을 할 수 있는지 연구한다. 특히 자원 제약이 있는 초기 탐색 단계에서 MLLMs이 인간의 선호도를 얼마나 잘 모방하여 개별 UI를 평가하고 비교할 수 있는지에 초점을 맞춘다. 30개의 UI에 대해 GPT-4o, Claude, Llama를 벤치마킹하고, 크라우드소싱 플랫폼에서 얻은 데이터를 사용하여 인간의 판단과 비교 분석했다.
시사점, 한계점
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MLLMs은 일부 UI 요소에 대해 인간의 선호도를 근사하게 나타낼 수 있다.
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MLLMs은 다른 UI 요소에 대해서는 인간의 판단과 차이를 보였다.
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MLLMs은 초기 UX 연구를 보완하는 데 잠재력이 있다.
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MLLMs의 한계점은 아직 존재하며, 모든 측면에서 인간의 판단을 대체할 수 없다.
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