/
/
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。
HPC Digital Twins for Evaluating Scheduling Policies, Incentive Structures and their Impact on Power and Cooling
NLKI: A lightweight Natural Language Knowledge Integration Framework for Improving Small VLMs in Commons VQA Tasks
Interact-Custom: Customized Human Object Interaction Image Generation
A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation
MIDAS: Multimodal Interactive Digital-humAn Synthesis via Real-time Autoregressive Video Generation
From Tabula Rasa to Emergent Abilities: Discovering Robot Skills via Real-World Unsupervised Quality-Diversity
Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks
STDiff: A State Transition Diffusion Framework for Time Series Imputation in Industrial Systems
LLMs Can't Handle Peer Pressure: Crumbling under Multi-Agent Social Interactions
Graph-R1: Incentivizing the Zero-Shot Graph Learning Capability in LLMs via Explicit Reasoning
Modality-Specific Speech Enhancement and Noise-Adaptive Fusion for Acoustic and Body-Conduction Microphone Framework
Humans Perceive Wrong Narratives from AI Reasoning Texts
SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning
Pareto Actor-Critic for Communication and Computation Co-Optimization in Non-Cooperative Federated Learning Services
Learning to Drive Ethically: Embedding Moral Reasoning into Autonomous Driving
Generative AI Against Poaching: Latent Composite Flow Matching for Wildlife Conservation
Privacy-Aware Detection of Fake Identity Documents: Methodology, Benchmark, and Improved Algorithms (FakeIDet2)
Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics
Steering Towards Fairness: Mitigating Political Bias in LLMs
Dynamic Context Compression for Efficient RAG
Irredundant $k$-Fold Cross-Validation
Prompt Engineering and the Effectiveness of Large Language Models in Enhancing Human Productivity
A Highly Clean Recipe Dataset with Ingredient States Annotation for State Probing Task
Entropy-Memorization Law: Evaluating Memorization Difficulty of Data in LLMs
The Joys of Categorical Conformal Prediction
Adversarial Manipulation of Reasoning Models using Internal Representations
Agent-to-Agent Theory of Mind: Testing Interlocutor Awareness among Large Language Models
A Hybrid Artificial Intelligence Method for Estimating Flicker in Power Systems (Changes are marked)
GLProtein: Global-and-Local Structure Aware Protein Representation Learning
Program Semantic Inequivalence Game with Large Language Models
DSO: Aligning 3D Generators with Simulation Feedback for Physical Soundness
Improving Quantization with Post-Training Model Expansion
Safe and Efficient Social Navigation through Explainable Safety Regions Based on Topological Features
A Simple Approach to Constraint-Aware Imitation Learning with Application to Autonomous Racing
Federated nnU-Net for Privacy-Preserving Medical Image Segmentation
ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation
Enhancing Automated Loop Invariant Generation for Complex Programs with Large Language Models
RevPRAG: Revealing Poisoning Attacks in Retrieval-Augmented Generation through LLM Activation Analysis
Categorical Data Clustering via Value Order Estimated Distance Metric Learning
Application of AI to formal methods - an analysis of current trends
Reconsidering the Performance of GAE in Link Prediction
See then Tell: Enhancing Key Information Extraction with Vision Grounding
Enhancing Natural Language Inference Performance with Knowledge Graph for COVID-19 Automated Fact-Checking in Indonesian Language
Puppet-Master: Scaling Interactive Video Generation as a Motion Prior for Part-Level Dynamics
FFHFlow: Diverse and Uncertainty-Aware Dexterous Grasp Generation via Flow Variational Inference
SoAy: A Solution-based LLM API-using Methodology for Academic Information Seeking
Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study
Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off
Network Formation and Dynamics Among Multi-LLMs
NetGPT: Generative Pretrained Transformer for Network Traffic
OLKAVS: An Open Large-Scale Korean Audio-Visual Speech Dataset
Explainability of Text Processing and Retrieval Methods: A Survey
The Ramon Llull's Thinking Machine for Automated Ideation
RLMR: Reinforcement Learning with Mixed Rewards for Creative Writing
LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence
MSARL: Decoupling Reasoning and Tool Use with Multi-Small-Agent Reinforcement Learning
Automated Algorithmic Discovery for Gravitational-Wave Detection Guided by LLM-Informed Evolutionary Monte Carlo Tree Search
Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess
Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground
Possible Principles for Aligned Structure Learning Agents
OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale
Prompt-to-Product: Generative Assembly via Bimanual Manipulation
OnGoal: Tracking and Visualizing Conversational Goals in Multi-Turn Dialogue with Large Language Models
Mixture of Contexts for Long Video Generation
FakeParts: a New Family of AI-Generated DeepFakes
Enabling Equitable Access to Trustworthy Financial Reasoning
Veritas: Generalizable Deepfake Detection via Pattern-Aware Reasoning
Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop
Inference-Time Alignment Control for Diffusion Models with Reinforcement Learning Guidance
ChainReaction! Structured Approach with Causal Chains as Intermediate Representations for Improved and Explainable Causal Video Question Answering
Train-Once Plan-Anywhere Kinodynamic Motion Planning via Diffusion Trees
ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts
WoW-Bench: Evaluating Fine-Grained Acoustic Perception in Audio-Language Models via Marine Mammal Vocalizations
ProactiveEval: A Unified Evaluation Framework for Proactive Dialogue Agents
Research Challenges in Relational Database Management Systems for LLM Queries
Quantum Verifiable Rewards for Post-Training Qiskit Code Assistant
AI Agentic Vulnerability Injection And Transformation with Optimized Reasoning
JADES: A Universal Framework for Jailbreak Assessment via Decompositional Scoring
Learning Primitive Embodied World Models: Towards Scalable Robotic Learning
Multi-Agent Penetration Testing AI for the Web
Uncertainty Aware-Predictive Control Barrier Functions: Safer Human Robot Interaction through Probabilistic Motion Forecasting
Exploring Machine Learning and Language Models for Multimodal Depression Detection
Speech Emotion Recognition via Entropy-Aware Score Selection
Surfel-based 3D Registration with Equivariant SE(3) Features
Evaluating Compositional Generalisation in VLMs and Diffusion Models
Safer Skin Lesion Classification with Global Class Activation Probability Map Evaluation and SafeML
Unleashing Uncertainty: Efficient Machine Unlearning for Generative AI
Signs of Struggle: Spotting Cognitive Distortions across Language and Register
Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection
Looking Beyond the Obvious: A Survey on Abstract Concept Recognition for Video Understanding
SKGE-SWIN: End-To-End Autonomous Vehicle Waypoint Prediction and Navigation Using Skip Stage Swin Transformer
Occlusion Robustness of CLIP for Military Vehicle Classification
SeqVLM: Proposal-Guided Multi-View Sequences Reasoning via VLM for Zero-Shot 3D Visual Grounding
Provable Benefits of In-Tool Learning for Large Language Models
${C}^{3}$-GS: Learning Context-aware, Cross-dimension, Cross-scale Feature for Generalizable Gaussian Splatting
Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol
EEGDM: Learning EEG Representation with Latent Diffusion Model
Generative Annotation for ASR Named Entity Correction
MobileCLIP2: Improving Multi-Modal Reinforced Training
Task Allocation for Autonomous Machines using Computational Intelligence and Deep Reinforcement Learning
Load more
LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence
Created by
Haebom
作者
Alisa Vinogradova (Optic Inc), Vlad Vinogradov (Optic Inc), Dmitrii Radkevich (Optic Inc), Ilya Yasny (Optic Inc), Dmitry Kobyzev (Optic Inc), Ivan Izmailov (Optic Inc), Katsiaryna Yanchanka (Optic Inc ), Roman (Optic Inc)
概要
この論文は、迅速な医薬品資産の実証のためのエージェントベースのAIシステム内で使用される競合他社の発見コンポーネントを説明し、ベンチマークします。競合他社の発見AIエージェントは、特定の適応症が与えられると、その適応症の競合環境を構成するすべての薬物を検索し、これらの薬物の標準的な属性を抽出します。競合他社の定義は投資家によって異なり、データは有料/ライセンスが付与され、レジストリ間で分割され、適応症によってオントロジーが一致せず、薬物名にエイリアスが多く、マルチモードで、急速に変化します。現在、LLMベースのAIシステムはこの問題のための最良のツールと考えられていますが、競合するすべての薬物名を確実に検索することはできません。評価の欠如を解決するために、本論文では、LLMベースのエージェントを使用して、プライベートバイオテックVCファンドの5年間のマルチモード非定型実写メモを、適応症を標準化された属性を持つ競合薬にマッピングする構造化評価コーパスに変換します。さらに、精度を最大化し、幻覚を抑制するために、予測された競合他社のリストから誤検知を除外する競合他社検証LLM-as-a-judgeエージェントを導入しました。このベンチマークでは、競合他社発見エージェントは83％の再現率を達成し、OpenAI Deep Research（65％）とPerplexity Labs（60％）を上回ります。このシステムは企業ユーザーを対象に運営されています。 Biotech VC投資ファンドを対象としたケーススタディでは、アナリストの処理時間が競合分析に対して2.5日から約3時間（約20倍）に短縮されました。
Takeaways、Limitations
•
Takeaways：
LLMベースのエージェントを利用して、マルチモードの非定型データを構造化データに変換し、競合薬物発見の精度を高める効果的な方法を提示します。実際の投資環境での適用により分析時間を大幅に短縮する実用的な成果を実証。新しいベンチマークデータセットを提示し、今後の研究の発展に貢献。
•
Limitations：
使用されるデータは特定のバイオテックVCファンドのデータに限定され、一般化の可能性を検証する必要があります。 LLM-as-a-judgeエージェントのパフォーマンスの追加分析と検証が必要です。競合他社の定義が投資家によって異なることは、システムの一般化に制約として作用する可能性があります。データの継続的な変化に対するシステムの適応性に関するさらなる研究の必要性
PDFを見る
Made with Slashpage
