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Daily Arxiv
Daily Arxiv
世界中で発行される人工知能関連の論文をまとめるページです。
このページはGoogle Geminiを活用して要約し、非営利で運営しています。
論文の著作権は著者および関連機関にあり、共有する際は出典を明記してください。
Boundary-Guided Policy Optimization for Memory-efficient RL of Diffusion Large Language Models
ManiAgent: An Agentic Framework for General Robotic Manipulation
AndesVL Technical Report: An Efficient Mobile-side Multimodal Large Language Model
ParsVoice: A Large-Scale Multi-Speaker Persian Speech Corpus for Text-to-Speech Synthesis
Optimally Deep Networks - Adapting Model Depth to Datasets for Superior Efficiency
BrowserAgent: Building Web Agents with Human-Inspired Web Browsing Actions
AGENTIQL: An Agent-Inspired Multi-Expert Framework for Text-to-SQL Generation
Towards Safe Maneuvering of Double-Ackermann-Steering Robots with a Soft Actor-Critic Framework
The Algorithmic Regulator
HccePose(BF): Predicting Front & Back Surfaces to Construct Ultra-Dense 2D-3D Correspondences for Pose Estimation
ICL-Router: In-Context Learned Model Representations for LLM Routing
CrisiText: A dataset of warning messages for LLM training in emergency communication
GTCN-G: A Residual Graph-Temporal Fusion Network for Imbalanced Intrusion Detection (Preprint)
Scalable Policy-Based RL Algorithms for POMDPs
OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT
Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain
AgentBuilder: Exploring Scaffolds for Prototyping User Experiences of Interface Agents
Neon: Negative Extrapolation From Self-Training Improves Image Generation
Triplet-Structured Knowledge Integration for Multi-Turn Medical Reasoning
General Exploratory Bonus for Optimistic Exploration in RLHF
PolySim: Bridging the Sim-to-Real Gap for Humanoid Control via Multi-Simulator Dynamics Randomization
Asymmetric Proximal Policy Optimization: mini-critics boost LLM reasoning
Graph2Eval: Automatic Multimodal Task Generation for Agents via Knowledge Graphs
Understanding Language Prior of LVLMs by Contrasting Chain-of-Embedding
Large language models management of medications: three performance analyses
Responsible AI Technical Report
A Longitudinal Randomized Control Study of Companion Chatbot Use: Anthropomorphism and Its Mediating Role on Social Impacts
SPiDR: A Simple Approach for Zero-Shot Safety in Sim-to-Real Transfer
TISDiSS: A Training-Time and Inference-Time Scalable Framework for Discriminative Source Separation
Efficient and Versatile Model for Multilingual Information Retrieval of Islamic Text: Development and Deployment in Real-World Scenarios
StegOT: Trade-offs in Steganography via Optimal Transport
General Demographic Foundation Models for Enhancing Predictive Performance Across Diseases and Populations
Attention as an Adaptive Filter
Diffusion Language Models Know the Answer Before Decoding
NinA: Normalizing Flows in Action. Training VLA Models with Normalizing Flows
Hard Examples Are All You Need: Maximizing GRPO Post-Training Under Annotation Budgets
AdaptJobRec: Enhancing Conversational Career Recommendation through an LLM-Powered Agentic System
An Introduction to Sliced Optimal Transport
EMSEdit: Efficient Multi-Step Meta-Learning-based Model Editing
DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting
MmWave Radar-Based Non-Line-of-Sight Pedestrian Localization at T-Junctions Utilizing Road Layout Extraction via Camera
Capturing More: Learning Multi-Domain Representations for Robust Online Handwriting Verification
A Cooperative Approach for Knowledge-based Business Process Design in a Public Authority
Finding Dori: Memorization in Text-to-Image Diffusion Models Is Not Local
Feature Distillation is the Better Choice for Model-Heterogeneous Federated Learning
Knowledge Fusion via Bidirectional Information Aggregation
LearnLens: LLM-Enabled Personalised, Curriculum-Grounded Feedback with Educators in the Loop
Dual Perspectives on Non-Contrastive Self-Supervised Learning
SAFER: Probing Safety in Reward Models with Sparse Autoencoder
Inverse Design in Nanophotonics via Representation Learning
SPADE: Spatial Transcriptomics and Pathology Alignment Using a Mixture of Data Experts for an Expressive Latent Space
VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents
Time-IMM: A Dataset and Benchmark for Irregular Multimodal Multivariate Time Series
BridgeVLA: Input-Output Alignment for Efficient 3D Manipulation Learning with Vision-Language Models
Uncertainty Estimation on Graphs with Structure Informed Stochastic Partial Differential Equations
EvolveNav: Empowering LLM-Based Vision-Language Navigation via Self-Improving Embodied Reasoning
Can LLMs Reason Structurally? An Evaluation via the Lens of Data Structures
Finite Sample Analysis of Linear Temporal Difference Learning with Arbitrary Features
Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models
Protein Design with Dynamic Protein Vocabulary
Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator
Steering Large Language Models for Machine Translation Personalization
AsynFusion: Towards Asynchronous Latent Consistency Models for Decoupled Whole-Body Audio-Driven Avatars
Joint Embedding vs Reconstruction: Provable Benefits of Latent Space Prediction for Self Supervised Learning
Fixed Point Explainability
Time Travel is Cheating: Going Live with DeepFund for Real-Time Fund Investment Benchmarking
MobileCity: An Efficient Framework for Large-Scale Urban Behavior Simulation
A Customized SAT-based Solver for Graph Coloring
Multi-Agent Autonomous Driving Systems with Large Language Models: A Survey of Recent Advances
FOCUS on Contamination: A Geospatial Deep Learning Framework with a Noise-Aware Loss for Surface Water PFAS Prediction
ParetoQ: Improving Scaling Laws in Extremely Low-bit LLM Quantization
Query Brand Entity Linking in E-Commerce Search
AgentBreeder: Mitigating the AI Safety Risks of Multi-Agent Scaffolds via Self-Improvement
GraphRAG under Fire
Polynomial-Time Algorithms for Fair Orientations of Chores
CiteBART: Learning to Generate Citations for Local Citation Recommendation
Reframing Image Difference Captioning with BLIP2IDC and Synthetic Augmentation
Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds
COMAL: A Convergent Meta-Algorithm for Aligning LLMs with General Preferences
Generative AI for Requirements Engineering: A Systematic Literature Review
Assessing Latency in ASR Systems: A Methodological Perspective for Real-Time Use
ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM Training
Exploring the Frontier of Vision-Language Models: A Survey of Current Methodologies and Future Directions
Offline Fictitious Self-Play for Competitive Games
When "Competency" in Reasoning Opens the Door to Vulnerability: Jailbreaking LLMs via Novel Complex Ciphers
Can ChatGPT support software verification?
Optimized Layerwise Approximation for Efficient Private Inference on Fully Homomorphic Encryption
DRIFT: Decompose, Retrieve, Illustrate, then Formalize Theorems
Adaptive Dual Reasoner: Large Reasoning Models Can Think Efficiently by Hybrid Reasoning
Concise Reasoning in the Lens of Lagrangian Optimization
Humanoid Artificial Consciousness Designed with Large Language Model Based on Psychoanalysis and Personality Theory
TripScore: Benchmarking and rewarding real-world travel planning with fine-grained evaluation
Agent Learning via Early Experience
L2M-AID: Autonomous Cyber-Physical Defense by Fusing Semantic Reasoning of Large Language Models with Multi-Agent Reinforcement Learning (Preprint)
Clean First, Align Later: Benchmarking Preference Data Cleaning for Reliable LLM Alignment
Similarity Field Theory: A Mathematical Framework for Intelligence
Large Language Models in Operations Research: Methods, Applications, and Challenges
MoEs Are Stronger than You Think: Hyper-Parallel Inference Scaling with RoE
Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining
MapAgent: A Hierarchical Agent for Geospatial Reasoning with Dynamic Map Tool Integration
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SPADE: Spatial Transcriptomics and Pathology Alignment Using a Mixture of Data Experts for an Expressive Latent Space
Created by
Haebom
作者
Ekaterina Redekop, Mara Pleasure, Zichen Wang, Kimberly Flores, Anthony Sisk, William Speier, Corey W. Arnold
概要
デジタル病理学の急速な成長と自己指導の深層学習の進歩により、さまざまな病気の基礎モデルの開発が可能になりました。さまざまなデータソースを統合するマルチモーダルアプローチが登場しましたが、スライドイメージ全体（WSI）と空間転写物学（ST）を包括的に統合する上で重要なギャップがあります。これは、標準的なヘマトキシリン＆エオシン（H＆E）染色を超えて重要な分子的不均一性を捉えるために不可欠です。本論文では、形態学的情報と分子情報を統合して単一の潜在空間で画像表現学習を導く基礎モデルであるSPADEを紹介します。 SPADEは、コントラスト学習を使用して共同登録されたWSIパッチと遺伝子発現プロファイルの表現を学習するために、2段階の画像特徴空間クラスタリングを介して専門家が生成する混合データ専門家技術を利用します。包括的なHEST-1kデータセットで事前トレーニングされたSPADEは、20のダウンストリーム操作で評価され、基本モデルよりも著しく優れた少数ショット性能を示し、形態学的および分子情報を1つの潜在空間に統合するという利点を強調します。
Takeaways、Limitations
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Takeaways:
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WSIとSTデータを統合する新しい基礎モデルであるSPADE開発。
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混合データのエキスパート技術を活用した画像表現学習の改善
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HEST-1kデータセットで事前トレーニングされたSPADEの優れた少数ショット性能を実証。
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形態学的および分子的情報統合の重要性の強調
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Limitations：
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本稿では具体的なLimitationsは直接言及されていません。
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追加の研究や他のデータセットの検証が必要です。
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モデルの一般化能力の追加評価が必要
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