Daily Arxiv

This page organizes papers related to artificial intelligence published around the world.
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LLMs for Automated Unit Test Generation and Assessment in Java: The AgoneTest Framework

BengaliFig: A Low-Resource Challenge for Figurative and Culturally Grounded Reasoning in Bengali

R3A: Reliable RTL Repair Framework with Multi-Agent Fault Localization and Stochastic Tree-of-Thoughts Patch Generation

EmoFeedback$^2$: Reinforcement of Continuous Emotional Image Generation via LVLM-based Reward and Textual Feedback

Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning

A Systematic Analysis of Large Language Models with RAG-enabled Dynamic Prompting for Medical Error Detection and Correction

TiCT: A Synthetically Pre-Trained Foundation Model for Time Series Classification

TREASURE: A Transformer-Based Foundation Model for High-Volume Transaction Understanding

Human Experts' Evaluation of Generative AI for Contextualizing STEAM Education in the Global South

Pistachio: Towards Synthetic, Balanced, and Long-Form Video Anomaly Benchmarks

PrefixGPT: Prefix Adder Optimization by a Generative Pre-trained Transformer

UniGame: Turning a Unified Multimodal Model Into Its Own Adversary

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

Adversarial Attack-Defense Co-Evolution for LLM Safety Alignment via Tree-Group Dual-Aware Search and Optimization

Uncertainty-Aware Deep Learning Framework for Remaining Useful Life Prediction in Turbofan Engines with Learned Aleatoric Uncertainty

ConceptGuard: Proactive Safety in Text-and-Image-to-Video Generation through Multimodal Risk Detection

CLLMRec: LLM-powered Cognitive-Aware Concept Recommendation via Semantic Alignment and Prerequisite Knowledge Distillation

TimeViper: A Hybrid Mamba-Transformer Vision-Language Model for Efficient Long Video Understanding

Think Visually, Reason Textually: Vision-Language Synergy in ARC

Cheating Stereo Matching in Full-scale: Physical Adversarial Attack against Binocular Depth Estimation in Autonomous Driving

Passive Dementia Screening via Facial Temporal Micro-Dynamics Analysis of In-the-Wild Talking-Head Video

Lost in Serialization: Invariance and Generalization of LLM Graph Reasoners

DensiCrafter: Physically-Constrained Generation and Fabrication of Self-Supporting Hollow Structures

Diffusion Models at the Drug Discovery Frontier: A Review on Generating Small Molecules versus Therapeutic Peptides

SARVLM: A Vision Language Foundation Model for Semantic Understanding and Target Recognition in SAR Imagery

Weak-to-Strong Generalization under Distribution Shifts

LightMem: Lightweight and Efficient Memory-Augmented Generation

SaFiRe: Saccade-Fixation Reiteration with Mamba for Referring Image Segmentation

Automated Neural Architecture Design for Industrial Defect Detection

PointNSP: Autoregressive 3D Point Cloud Generation with Next-Scale Level-of-Detail Prediction

Uncovering Implicit Bias in Large Language Models with Concept Learning Dataset

The Impossibility of Inverse Permutation Learning in Transformer Models

Mechanism of Task-oriented Information Removal in In-context Learning

A Unified Noise-Curvature View of Loss of Trainability

Modular, On-Site Solutions with Lightweight Anomaly Detection for Sustainable Nutrient Management in Agriculture

Not All Splits Are Equal: Rethinking Attribute Generalization Across Unrelated Categories

Equivariant Flow Matching for Symmetry-Breaking Bifurcation Problems

Consistent Opponent Modeling of Static Opponents in Imperfect-Information Games

Special-Character Adversarial Attacks on Open-Source Language Model

Where to Start Alignment? Diffusion Large Language Model May Demand a Distinct Position

WeatherDiffusion: Controllable Weather Editing in Intrinsic Space

Empowering Time Series Forecasting with LLM-Agents

Contrast-Prior Enhanced Duality for Mask-Free Shadow Removal

AutoDiscovery: Open-ended Scientific Discovery via Bayesian Surprise

Fair Algorithms with Probing for Multi-Agent Multi-Armed Bandits

Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor

UITron-Speech: Towards Automated GUI Agents Based on Speech Instructions

Flow Matching Meets PDEs: A Unified Framework for Physics-Constrained Generation

Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints

IVY-FAKE: A Unified Explainable Framework and Benchmark for Image and Video AIGC Detection

LCB-CV-UNet: Enhanced Detector for High Dynamic Range Radar Signals

Characterizing Pattern Matching and Its Limits on Compositional Task Structures

Force Prompting: Video Generation Models Can Learn and Generalize Physics-based Control Signals

How Do Companies Manage the Environmental Sustainability of AI? An Interview Study About Green AI Efforts and Regulations

MigGPT: Harnessing Large Language Models for Automated Migration of Out-of-Tree Linux Kernel Patches Across Versions

Reasoning Transfer for an Extremely Low-Resource and Endangered Language: Bridging Languages Through Sample-Efficient Language Understanding

OuroMamba: A Data-Free Quantization Framework for Vision Mamba

TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster

Bridging Critical Gaps in Convergent Learning: How Representational Alignment Evolves Across Layers, Training, and Distribution Shifts

Personalized Image Generation for Recommendations Beyond Catalogs

Without Paired Labeled Data: End-to-End Self-Supervised Learning for Drone-view Geo-Localization

Meursault as a Data Point

Adaptive Object Detection for Indoor Navigation Assistance: A Performance Evaluation of Real-Time Algorithms

CroMe: Multimodal Fake News Detection using Cross-Modal Tri-Transformer and Metric Learning

BoundingDocs: a Unified Dataset for Document Question Answering with Spatial Annotations

Beyond Introspection: Reinforcing Thinking via Externalist Behavioral Feedback

Multi-PA: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models

Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models

CoxKAN: Kolmogorov-Arnold Networks for Interpretable, High-Performance Survival Analysis

A Gray-box Attack against Latent Diffusion Model-based Image Editing by Posterior Collapse

SOAP: Enhancing Spatio-Temporal Relation and Motion Information Capturing for Few-Shot Action Recognition

Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness

Safety Control of Service Robots with LLMs and Embodied Knowledge Graphs

Data Valuation by Fusing Global and Local Statistical Information

Natural Strategic Ability in Stochastic Multi-Agent Systems

Dual-Balancing for Multi-Task Learning

ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition

PaTAS: A Parallel System for Trust Propagation in Neural Networks Using Subjective Logic

FRAGMENTA: End-to-end Fragmentation-based Generative Model with Agentic Tuning for Drug Lead Optimization

Universe of Thoughts: Enabling Creative Reasoning with Large Language Models

Failure Modes in LLM Systems: A System-Level Taxonomy for Reliable AI Applications

Simulated Self-Assessment in Large Language Models: A Psychometric Approach to AI Self-Efficacy

KRAL: Knowledge and Reasoning Augmented Learning for LLM-assisted Clinical Antimicrobial Therapy

Step-Audio-R1 Technical Report

Heterogeneous Multi-Agent Proximal Policy Optimization for Power Distribution System Restoration

Operationalizing Pluralistic Values in Large Language Model Alignment Reveals Trade-offs in Safety, Inclusivity, and Model Behavior

Augur: Modeling Covariate Causal Associations in Time Series via Large Language Models

CoMind: Towards Community-Driven Agents for Machine Learning Engineering

Safe and Economical UAV Trajectory Planning in Low-Altitude Airspace: A Hybrid DRL-LLM Approach with Compliance Awareness

Learning Individual Behavior in Agent-Based Models with Graph Diffusion Networks

Co-PatcheR: Collaborative Software Patching with Component(s)-specific Small Reasoning Models

Earth Observation Satellite Scheduling with Graph Neural Networks and Monte Carlo Tree Search

Revisiting Generalization Across Difficulty Levels: It's Not So Easy

ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration

G$^2$VLM: Geometry Grounded Vision Language Model with Unified 3D Reconstruction and Spatial Reasoning

Matrix: Peer-to-Peer Multi-Agent Synthetic Data Generation Framework

Through the telecom lens: Are all training samples important?

Escaping the Verifier: Learning to Reason via Demonstrations

Attention-Guided Patch-Wise Sparse Adversarial Attacks on Vision-Language-Action Models

Continual Error Correction on Low-Resource Devices

Diffusion Models at the Drug Discovery Frontier: A Review on Generating Small Molecules versus Therapeutic Peptides

Created by

Haebom

저자

Yiquan Wang, Yahui Ma, Yuhan Chang, Jiayao Yan, Jialin Zhang, Minnuo Cai, Kai Wei

개요

확산 모델은 생성 모델링 분야에서 선도적인 프레임워크로 부상했으며, 약물 발견의 전통적으로 느리고 비용이 많이 드는 프로세스를 혁신할 준비가 되어 있습니다. 이 논문은 두 가지 주요 치료 방식인 저분자 및 치료용 펩타이드 설계에 대한 확산 모델의 적용을 체계적으로 비교합니다. 반복적 디노이징의 통합 프레임워크가 각 방식의 고유한 분자 표현, 화학 공간 및 설계 목표에 어떻게 적용되는지 분석합니다. 저분자의 경우, 이러한 모델은 구조 기반 설계에 뛰어나며, 원하는 물리화학적 특성을 가진 새롭고 포켓에 맞는 리간드를 생성하지만, 화학적 합성 가능성을 보장하는 데 중요한 어려움에 직면합니다. 반대로, 치료용 펩타이드의 경우, 기능적 서열 생성 및 de novo 구조 설계에 초점을 맞추며, 주요 과제는 단백질 분해에 대한 생물학적 안정성 확보, 적절한 폴딩 보장 및 면역원성 최소화입니다. 이러한 뚜렷한 과제에도 불구하고, 두 분야 모두 공통적인 어려움에 직면합니다: 고품질 실험 데이터 부족, 검증을 위한 부정확한 스코어링 함수 의존성, 그리고 실험적 검증의 중요한 필요성. 결론적으로 확산 모델의 잠재력은 이러한 방식별 격차를 해소하고 자동화된, 폐쇄 루프 설계-제작-테스트-학습(DBTL) 플랫폼에 통합함으로써, 단순한 화학적 탐구를 넘어 새로운 치료법의 온디맨드 엔지니어링으로 패러다임을 전환함으로써 실현될 것입니다.

시사점, 한계점

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시사점:

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확산 모델은 저분자 및 치료용 펩타이드 설계 모두에서 유망한 접근 방식을 제시함.

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구조 기반 설계, 기능적 서열 생성, de novo 구조 설계에 활용 가능.

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약물 발견 프로세스 가속화 및 효율성 향상 가능성 제시.

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DBTL 플랫폼 통합을 통한 자동화된 약물 설계 가능성 제시.

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한계점:

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고품질 실험 데이터 부족.

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정확하지 않은 스코어링 함수에 대한 의존성.

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실험적 검증의 필요성.

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저분자: 화학적 합성 가능성 확보의 어려움.

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치료용 펩타이드: 생물학적 안정성 확보, 적절한 폴딩 보장, 면역원성 최소화의 어려움.

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