Saved in:
| Main Authors: | Rudd, Ethan M., Andrews, Christopher, Tully, Philip |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.13023 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On Distributional Reinforcement Learning in Chaotic Dynamical Systems
by: Rudd-Jones, James, et al.
Published: (2026)
by: Rudd-Jones, James, et al.
Published: (2026)
Can LLMs Guide Their Own Exploration? Gradient-Guided Reinforcement Learning for LLM Reasoning
by: Liang, Zhenwen, et al.
Published: (2025)
by: Liang, Zhenwen, et al.
Published: (2025)
On Evaluating LLM Alignment by Evaluating LLMs as Judges
by: Liu, Yixin, et al.
Published: (2025)
by: Liu, Yixin, et al.
Published: (2025)
Fine-tuning Timeseries Predictors Using Reinforcement Learning
by: Cazaux, Hugo, et al.
Published: (2026)
by: Cazaux, Hugo, et al.
Published: (2026)
From Theory to Practice: Implementing and Evaluating e-Fold Cross-Validation
by: Mahlich, Christopher, et al.
Published: (2024)
by: Mahlich, Christopher, et al.
Published: (2024)
Data Distribution as a Lever for Guiding Optimizers Toward Superior Generalization in LLMs
by: Gangavarapu, Tushaar, et al.
Published: (2026)
by: Gangavarapu, Tushaar, et al.
Published: (2026)
Can LLMs Help You at Work? A Sandbox for Evaluating LLM Agents in Enterprise Environments
by: Vishwakarma, Harsh, et al.
Published: (2025)
by: Vishwakarma, Harsh, et al.
Published: (2025)
VoyagerVision: Investigating the Role of Multi-modal Information for Open-ended Learning Systems
by: Smyth, Ethan, et al.
Published: (2025)
by: Smyth, Ethan, et al.
Published: (2025)
Are LLMs The Way Forward? A Case Study on LLM-Guided Reinforcement Learning for Decentralized Autonomous Driving
by: Anvar, Timur, et al.
Published: (2025)
by: Anvar, Timur, et al.
Published: (2025)
Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs
by: Knoop, Jonathan, et al.
Published: (2026)
by: Knoop, Jonathan, et al.
Published: (2026)
Evidence for Limited Metacognition in LLMs
by: Ackerman, Christopher
Published: (2025)
by: Ackerman, Christopher
Published: (2025)
Who Judges the Judge? LLM Jury-on-Demand: Building Trustworthy LLM Evaluation Systems
by: Li, Xiaochuan, et al.
Published: (2025)
by: Li, Xiaochuan, et al.
Published: (2025)
Attacks and Defenses Against LLM Fingerprinting
by: Kurian, Kevin, et al.
Published: (2025)
by: Kurian, Kevin, et al.
Published: (2025)
One-shot Federated Learning Methods: A Practical Guide
by: Liu, Xiang, et al.
Published: (2025)
by: Liu, Xiang, et al.
Published: (2025)
Learning in Context, Guided by Choice: A Reward-Free Paradigm for Reinforcement Learning with Transformers
by: Dong, Juncheng, et al.
Published: (2026)
by: Dong, Juncheng, et al.
Published: (2026)
A Justice Lens on Fairness and Ethics Courses in Computing Education: LLM-Assisted Multi-Perspective and Thematic Evaluation
by: Andrews, Kenya S., et al.
Published: (2025)
by: Andrews, Kenya S., et al.
Published: (2025)
But what is your honest answer? Aiding LLM-judges with honest alternatives using steering vectors
by: Eshuijs, Leon, et al.
Published: (2025)
by: Eshuijs, Leon, et al.
Published: (2025)
GPU Kernel Scientist: An LLM-Driven Framework for Iterative Kernel Optimization
by: Andrews, Martin, et al.
Published: (2025)
by: Andrews, Martin, et al.
Published: (2025)
REASONING COMPILER: LLM-Guided Optimizations for Efficient Model Serving
by: Tang, Annabelle Sujun, et al.
Published: (2025)
by: Tang, Annabelle Sujun, et al.
Published: (2025)
On the Importance of Task Complexity in Evaluating LLM-Based Multi-Agent Systems
by: Tang, Bohan, et al.
Published: (2025)
by: Tang, Bohan, et al.
Published: (2025)
A Comprehensive Guide to Explainable AI: From Classical Models to LLMs
by: Hsieh, Weiche, et al.
Published: (2024)
by: Hsieh, Weiche, et al.
Published: (2024)
Mutation-Guided LLM-based Test Generation at Meta
by: Foster, Christopher, et al.
Published: (2025)
by: Foster, Christopher, et al.
Published: (2025)
A Guide to Failure in Machine Learning: Reliability and Robustness from Foundations to Practice
by: Heim, Eric, et al.
Published: (2025)
by: Heim, Eric, et al.
Published: (2025)
AutoOR: Scalably Post-training LLMs to Autoformalize Operations Research Problems
by: Motwani, Sumeet Ramesh, et al.
Published: (2026)
by: Motwani, Sumeet Ramesh, et al.
Published: (2026)
Property-Guided LLM Program Synthesis for Planning
by: Pereira, André G., et al.
Published: (2026)
by: Pereira, André G., et al.
Published: (2026)
FHE-Agent: Automating CKKS Configuration for Practical Encrypted Inference via an LLM-Guided Agentic Framework
by: Xu, Nuo, et al.
Published: (2025)
by: Xu, Nuo, et al.
Published: (2025)
DAG-Math: Graph-of-Thought Guided Mathematical Reasoning in LLMs
by: Zhang, Yuanhe, et al.
Published: (2025)
by: Zhang, Yuanhe, et al.
Published: (2025)
Limits of PRM-Guided Tree Search for Mathematical Reasoning with LLMs
by: Cinquin, Tristan, et al.
Published: (2025)
by: Cinquin, Tristan, et al.
Published: (2025)
The Agentic Researcher: A Practical Guide to AI-Assisted Research in Mathematics and Machine Learning
by: Zimmer, Max, et al.
Published: (2026)
by: Zimmer, Max, et al.
Published: (2026)
How Can LLM Guide RL? A Value-Based Approach
by: Zhang, Shenao, et al.
Published: (2024)
by: Zhang, Shenao, et al.
Published: (2024)
Evaluation and Benchmarking of LLM Agents: A Survey
by: Mohammadi, Mahmoud, et al.
Published: (2025)
by: Mohammadi, Mahmoud, et al.
Published: (2025)
Robust Guided Diffusion for Offline Black-Box Optimization
by: Chen, Can Sam, et al.
Published: (2024)
by: Chen, Can Sam, et al.
Published: (2024)
Anticipatory Evaluation of Language Models
by: Park, Jungsoo, et al.
Published: (2025)
by: Park, Jungsoo, et al.
Published: (2025)
MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale Deployment
by: Huang, Hanxian, et al.
Published: (2026)
by: Huang, Hanxian, et al.
Published: (2026)
OKG-LLM: Aligning Ocean Knowledge Graph with Observation Data via LLMs for Global Sea Surface Temperature Prediction
by: Yang, Hanchen, et al.
Published: (2025)
by: Yang, Hanchen, et al.
Published: (2025)
Policy Guided Tree Search for Enhanced LLM Reasoning
by: Li, Yang
Published: (2025)
by: Li, Yang
Published: (2025)
Process Reward Models for LLM Agents: Practical Framework and Directions
by: Choudhury, Sanjiban
Published: (2025)
by: Choudhury, Sanjiban
Published: (2025)
LLM Reasoning with Process Rewards for Outcome-Guided Steps
by: Rezaei, Mohammad, et al.
Published: (2026)
by: Rezaei, Mohammad, et al.
Published: (2026)
AI Biases as Asymmetries: A Review to Guide Practice
by: Waters, Gabriella, et al.
Published: (2025)
by: Waters, Gabriella, et al.
Published: (2025)
On Evaluating LLMs' Capabilities as Functional Approximators: A Bayesian Perspective
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2024)
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2024)
Similar Items
-
On Distributional Reinforcement Learning in Chaotic Dynamical Systems
by: Rudd-Jones, James, et al.
Published: (2026) -
Can LLMs Guide Their Own Exploration? Gradient-Guided Reinforcement Learning for LLM Reasoning
by: Liang, Zhenwen, et al.
Published: (2025) -
On Evaluating LLM Alignment by Evaluating LLMs as Judges
by: Liu, Yixin, et al.
Published: (2025) -
Fine-tuning Timeseries Predictors Using Reinforcement Learning
by: Cazaux, Hugo, et al.
Published: (2026) -
From Theory to Practice: Implementing and Evaluating e-Fold Cross-Validation
by: Mahlich, Christopher, et al.
Published: (2024)