Image de couverture de livre

ExLLM: Experience-Enhanced LLM Optimization for Molecular Design and Beyond

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ran, Nian, Wang, Yue, Zhang, Xiaoyuan, Li, Zhongzheng, Ran, Qingsong, Li, Wenhao, Allmendinger, Richard
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

MCCE: A Framework for Multi-LLM Collaborative Co-Evolution
par: Ran, Nian, et autres
Publié: (2025)

HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting
par: Ran, Nian, et autres
Publié: (2024)

Automated Flow Pattern Classification in Multi-phase Systems Using AI and Capacitance Sensing Techniques
par: Ran, Nian, et autres
Publié: (2025)

Multi-objective evolutionary GAN for tabular data synthesis
par: Ran, Nian, et autres
Publié: (2024)

Counterfactual Credit Guided Bayesian Optimization
par: Wei, Qiyu, et autres
Publié: (2025)

Learning Beyond Optimization: Stress-Gated Dynamical Regime Regulation in Autonomous Systems
par: Ran, Sheng
Publié: (2026)

Reference-guided Policy Optimization for Molecular Optimization via LLM Reasoning
par: Li, Xuan, et autres
Publié: (2026)

LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuits
par: Kochar, Dimple Vijay, et autres
Publié: (2024)

Beyond Single-Value Metrics: Evaluating and Enhancing LLM Unlearning with Cognitive Diagnosis
par: Lang, Yicheng, et autres
Publié: (2025)

Gradient-based Sample Selection for Faster Bayesian Optimization
par: Wei, Qiyu, et autres
Publié: (2025)

Designing Efficient LLM Accelerators for Edge Devices
par: Haris, Jude, et autres
Publié: (2024)

LLM Unlearning with LLM Beliefs
par: Li, Kemou, et autres
Publié: (2025)

Bayesian Generative Adversarial Networks via Gaussian Approximation for Tabular Data Synthesis
par: Nasution, Bahrul Ilmi, et autres
Publié: (2026)

ADO-LLM: Analog Design Bayesian Optimization with In-Context Learning of Large Language Models
par: Yin, Yuxuan, et autres
Publié: (2024)

Beyond Uniform SVD:Dual-Level Optimization across Columns and Modules for LLM Compression
par: Xv, Lin, et autres
Publié: (2025)

Beyond Next Token Probabilities: Learnable, Fast Detection of Hallucinations and Data Contamination on LLM Output Distributions
par: Bar-Shalom, Guy, et autres
Publié: (2025)

ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking
par: Li, Wenshuo, et autres
Publié: (2024)

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning
par: Lang, Yicheng, et autres
Publié: (2025)

ExPairT-LLM: Exact Learning for LLM Code Selection by Pairwise Queries
par: Yuviler, Tom, et autres
Publié: (2025)

An adaptive approach to Bayesian Optimization with switching costs
par: Pricopie, Stefan, et autres
Publié: (2024)

LLM4ED: Large Language Models for Automatic Equation Discovery
par: Du, Mengge, et autres
Publié: (2024)

ADO: Automatic Data Optimization for Inputs in LLM Prompts
par: Lin, Sam, et autres
Publié: (2025)

DrSR: LLM based Scientific Equation Discovery with Dual Reasoning from Data and Experience
par: Wang, Runxiang, et autres
Publié: (2025)

Beyond Numeric Rewards: In-Context Dueling Bandits with LLM Agents
par: Xia, Fanzeng, et autres
Publié: (2024)

Model-agnostic variable importance for predictive uncertainty: an entropy-based approach
par: Wood, Danny, et autres
Publié: (2023)

LARGO: Latent Adversarial Reflection through Gradient Optimization for Jailbreaking LLMs
par: Li, Ran, et autres
Publié: (2025)

FHE-Agent: Automating CKKS Configuration for Practical Encrypted Inference via an LLM-Guided Agentic Framework
par: Xu, Nuo, et autres
Publié: (2025)

MetaKube: An Experience-Aware LLM Framework for Kubernetes Failure Diagnosis
par: Sun, Wei, et autres
Publié: (2026)

HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving
par: Chen, Zhiwen, et autres
Publié: (2025)

Beyond Experience Retrieval: Learning to Generate Utility-Optimized Structured Experience for Frozen LLMs
par: Li, Xuancheng, et autres
Publié: (2026)

ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency
par: Yao, Yuhang, et autres
Publié: (2024)

Revisable by Design: A Theory of Streaming LLM Agent Execution
par: Zhai, Zhiyuan, et autres
Publié: (2026)

Distillation-Guided Structural Transfer for Continual Learning Beyond Sparse Distributed Memory
par: Xue, Huiyan, et autres
Publié: (2025)

Transformers in Pseudo-Random Number Generation: A Dual Perspective on Theory and Practice
par: Li, Ran, et autres
Publié: (2025)

Randomized Antipodal Search Done Right for Data Pareto Improvement of LLM Unlearning
par: Liu, Ziwen, et autres
Publié: (2026)

Enhancing LLM Agents for Code Generation with Possibility and Pass-rate Prioritized Experience Replay
par: Chen, Yuyang, et autres
Publié: (2024)

Spatial-Aware Decision-Making with Ring Attractors in Reinforcement Learning Systems
par: Saura, Marcos Negre, et autres
Publié: (2024)

LEKA:LLM-Enhanced Knowledge Augmentation
par: Zhang, Xinhao, et autres
Publié: (2025)

Semantic Energy: Detecting LLM Hallucination Beyond Entropy
par: Ma, Huan, et autres
Publié: (2025)

Capacity-Aware Mixture Law Enables Efficient LLM Data Optimization
par: Li, Jingwei, et autres
Publié: (2026)