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.

Batch Acquisition Function Evaluations and Decouple Optimizer Updates for Faster Bayesian Optimization

Physics-Informed Neural Networks for Nonlinear Output Regulation

Unlocking the Forgery Detection Potential of Vanilla MLLMs: A Novel Training-Free Pipeline

Generalized Denoising Diffusion Codebook Models (gDDCM): Tokenizing images using a pre-trained diffusion model

Rethinking Saliency Maps: A Cognitive Human Aligned Taxonomy and Evaluation Framework for Explanations

Dimension vs. Precision: A Comparative Analysis of Autoencoders and Quantization for Efficient Vector Retrieval on BEIR SciFact

UNSEEN: Enhancing Dataset Pruning from a Generalization Perspective

PFAvatar: Pose-Fusion 3D Personalized Avatar Reconstruction from Real-World Outfit-of-the-Day Photos

Optimal Look-back Horizon for Time Series Forecasting in Federated Learning

Fine-Grained Representation for Lane Topology Reasoning

VULPO: Context-Aware Vulnerability Detection via On-Policy LLM Optimization

A Meta-Heuristic Load Balancer for Cloud Computing Systems

Embedding Explainable AI in NHS Clinical Safety: The Explainability-Enabled Clinical Safety Framework (ECSF)

MedBuild AI: An Agent-Based Hybrid Intelligence Framework for Reshaping Agency in Healthcare Infrastructure Planning through Generative Design for Medical Architecture

MOON Embedding: Multimodal Representation Learning for E-commerce Search Advertising

Efficient Reinforcement Learning for Zero-Shot Coordination in Evolving Games

Who Gets the Reward, Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents

A Style is Worth One Code: Unlocking Code-to-Style Image Generation with Discrete Style Space

LocalBench: Benchmarking LLMs on County-Level Local Knowledge and Reasoning

LoopTool: Closing the Data-Training Loop for Robust LLM Tool Calls

Tele-LLM-Hub: Building Context-Aware Multi-Agent LLM Systems for Telecom Networks

FGM-HD: Boosting Generation Diversity of Fractal Generative Models through Hausdorff Dimension Induction

Energy Consumption of Dataframe Libraries for End-to-End Deep Learning Pipelines:A Comparative Analysis

Resilient by Design -- Active Inference for Distributed Continuum Intelligence

Resource Efficient Sleep Staging via Multi-Level Masking and Prompt Learning

Physics-Informed Neural Networks for Real-Time Gas Crossover Prediction in PEM Electrolyzers: First Application with Multi-Membrane Validation

MusRec: Zero-Shot Text-to-Music Editing via Rectified Flow and Diffusion Transformers

Leveraging LLM-based agents for social science research: insights from citation network simulations

Deploying Rapid Damage Assessments from sUAS Imagery for Disaster Response

DRIP: Defending Prompt Injection via Token-wise Representation Editing and Residual Instruction Fusion

Clone Deterministic 3D Worlds

Posterior Sampling by Combining Diffusion Models with Annealed Langevin Dynamics

MMEdge: Accelerating On-device Multimodal Inference via Pipelined Sensing and Encoding

FinVet: A Collaborative Framework of RAG and External Fact-Checking Agents for Financial Misinformation Detection

From Reasoning LLMs to BERT: A Two-Stage Distillation Framework for Search Relevance

PromptGuard at BLP-2025 Task 1: A Few-Shot Classification Framework Using Majority Voting and Keyword Similarity for Bengali Hate Speech Detection

A More Realistic Evaluation of Cross-Frequency Transfer Learning and Foundation Forecasting Models

Towards Sharper Object Boundaries in Self-Supervised Depth Estimation

Patent Language Model Pretraining with ModernBERT

Retrosynthesis Planning via Worst-path Policy Optimisation in Tree-structured MDPs

Efficient Decoding Methods for Language Models on Encrypted Data

Spectral Masking and Interpolation Attack (SMIA): A Black-box Adversarial Attack against Voice Authentication and Anti-Spoofing Systems

DepthVision: Enabling Robust Vision-Language Models with GAN-Based LiDAR-to-RGB Synthesis for Autonomous Driving

Automatic Differentiation of Agent-Based Models

Do Retrieval Augmented Language Models Know When They Don't Know?

Skill-Aligned Fairness in Multi-Agent Learning for Collaboration in Healthcare

Spatial Policy: Guiding Visuomotor Robotic Manipulation with Spatial-Aware Modeling and Reasoning

RynnEC: Bringing MLLMs into Embodied World

LENS: Learning to Segment Anything with Unified Reinforced Reasoning

MOON: Generative MLLM-based Multimodal Representation Learning for E-commerce Product Understanding

DIVER: A Multi-Stage Approach for Reasoning-intensive Information Retrieval

Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions

Dynamic User-controllable Privacy-preserving Few-shot Sensing Framework

LLMDistill4Ads: Using Cross-Encoders to Distill from LLM Signals for Advertiser Keyphrase Recommendations

SlotMatch: Distilling Object-Centric Representations for Unsupervised Video Segmentation

GAIS: Frame-Level Gated Audio-Visual Integration with Semantic Variance-Scaled Perturbation for Text-Video Retrieval

GMAT: Grounded Multi-Agent Clinical Description Generation for Text Encoder in Vision-Language MIL for Whole Slide Image Classification

AgentArmor: Enforcing Program Analysis on Agent Runtime Trace to Defend Against Prompt Injection

Cross-Domain Few-Shot Learning with Coalescent Projections and Latent Space Reservation

FastDINOv2: Frequency Based Curriculum Learning Improves Robustness and Training Speed

OptScale: Probabilistic Optimality for Inference-time Scaling

EvoLM: In Search of Lost Language Model Training Dynamics

Synthetic Geology: Structural Geology Meets Deep Learning

Foundation Models in Medical Imaging: A Review and Outlook

FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning

OG-VLA: Orthographic Image Generation for 3D-Aware Vision-Language Action Model

Scaling Textual Gradients via Sampling-Based Momentum

MCTSr-Zero: Self-Reflective Psychological Counseling Dialogues Generation via Principles and Adaptive Exploration

In-context Language Learning for Endangered Languages in Speech Recognition

SpecEdge: Scalable Edge-Assisted Serving Framework for Interactive LLMs

Preference Learning with Lie Detectors can Induce Honesty or Evasion

Anti-adversarial Learning: Desensitizing Prompts for Large Language Models

AdCare-VLM: Towards a Unified and Pre-aligned Latent Representation for Healthcare Video Understanding

Non-Uniform Class-Wise Coreset Selection for Vision Model Fine-tuning

ACoRN: Noise-Robust Abstractive Compression in Retrieval-Augmented Language Models

A Survey of Cross-domain Graph Learning: Progress and Future Directions

Availability-aware Sensor Fusion via Unified Canonical Space

ElementaryNet: A Non-Strategic Neural Network for Predicting Human Behavior in Normal-Form Games

1-Lipschitz Network Initialization for Certifiably Robust Classification Applications: A Decay Problem

Personalized Image Generation for Recommendations Beyond Catalogs

IPAD: Inverse Prompt for AI Detection - A Robust and Interpretable LLM-Generated Text Detector

MoM: Linear Sequence Modeling with Mixture-of-Memories

Rethinking Token-wise Feature Caching: Accelerating Diffusion Transformers with Dual Feature Caching

Automated Materials Discovery Platform Realized: Scanning Probe Microscopy of Combinatorial Libraries

Higher-Order Transformers With Kronecker-Structured Attention

Optimizing Federated Learning by Entropy-Based Client Selection

VisAidMath: Benchmarking Visual-Aided Mathematical Reasoning

Can Machines Think Like Humans? A Behavioral Evaluation of LLM Agents in Dictator Games

Generating Streamlining Constraints with Large Language Models

The Energy Cost of Artificial Intelligence Lifecycle in Communication Networks

KWT-Tiny: RISC-V Accelerated, Embedded Keyword Spotting Transformer

Benchmark on Drug Target Interaction Modeling from a Drug Structure Perspective

Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics

NAIST Academic Travelogue Dataset

SemCo: Toward Semantic Coherent Visual Relationship Forecasting

Multi-Agent Deep Research: Training Multi-Agent Systems with M-GRPO

Requirements for Aligned, Dynamic Resolution of Conflicts in Operational Constraints

CTRL-ALT-DECEIT: Sabotage Evaluations for Automated AI R&D

VSPO: Validating Semantic Pitfalls in Ontology via LLM-Based CQ Generation

Are We Asking the Right Questions? On Ambiguity in Natural Language Queries for Tabular Data Analysis

TxGemma: Efficient and Agentic LLMs for Therapeutics

Created by

Haebom

저자

Eric Wang, Samuel Schmidgall, Paul F. Jaeger, Fan Zhang, Rory Pilgrim, Yossi Matias, Joelle Barral, David Fleet, Shekoofeh Azizi

개요

TxGemma는 치료제 개발 과정에서 높은 실패율을 낮추기 위해 개발된, 효율적이고 일반적인 대규모 언어 모델(LLM) 모음입니다. 다양한 정보원을 통합하여 치료 특성 예측, 상호 작용적 추론 및 설명 가능성을 제공합니다. 2B, 9B, 27B 파라미터 모델로 구성되며, Gemma-2를 기반으로 소분자, 단백질, 핵산, 질병 및 세포주에 대한 종합적인 데이터 세트로 미세 조정되었습니다. 66가지 치료제 개발 과제에서 최첨단 일반 모델보다 64개 과제(45개 과제에서 우수), 최첨단 전문 모델보다 50개 과제(26개 과제에서 우수)에서 우수하거나 비슷한 성능을 달성했습니다. 또한, 자연어로 상호 작용하고, 분자 구조에 기반한 예측에 대한 기전적 추론을 제공하며, 과학적 논의에 참여할 수 있는 대화형 모델을 특징으로 합니다. Agentic-Tx는 Gemini 2.5를 기반으로 한 일반적인 치료제 에이전트 시스템으로, 추론, 행동, 다양한 워크플로 관리 및 외부 도메인 지식 획득 기능을 제공하며, Humanity's Last Exam 벤치마크(화학 및 생물학)에서 기존 최고 모델보다 성능이 향상되었습니다.

시사점, 한계점

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시사점:

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치료제 개발 과정의 효율성 향상 및 실패율 감소에 기여할 수 있음.

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다양한 치료제 개발 단계에 광범위하게 적용 가능함.

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기존 LLM보다 적은 훈련 데이터로 미세 조정 가능하여 데이터가 부족한 응용 분야에 적합함.

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자연어 기반 상호 작용 및 설명 가능성을 제공하여 과학자들의 연구를 지원함.

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Agentic-Tx는 다양한 워크플로우를 관리하고 외부 지식을 획득하여 복잡한 과제 해결에 도움을 줌.

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기존 최고 모델 대비 성능 향상을 보임.

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한계점:

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LLM 기반 모델의 일반적인 한계점(예: 데이터 편향, 예측의 신뢰성 문제)이 존재할 수 있음.

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모델의 성능은 사용된 데이터의 질과 양에 크게 의존적일 수 있음.

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복잡한 생물학적 과정에 대한 완전한 이해를 제공하지 못할 수 있음.

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새로운 약물 후보 물질의 발견 및 개발에 있어서 LLM의 역할에 대한 추가적인 검증이 필요함.

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