Copertina

BeamPERL: Parameter-Efficient RL with Verifiable Rewards Specializes Compact LLMs for Structured Beam Mechanics Reasoning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Hage, Tarjei Paule, Buehler, Markus J.
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence Materials Science Computation and Language Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

GraphAgents: Knowledge Graph-Guided Agentic AI for Cross-Domain Materials Design
di: Stewart, Isabella A., et al.
Pubblicazione: (2026)

Agentic Deep Graph Reasoning Yields Self-Organizing Knowledge Networks
di: Buehler, Markus J.
Pubblicazione: (2025)

Higher-Order Knowledge Representations for Agentic Scientific Reasoning
di: Stewart, Isabella A., et al.
Pubblicazione: (2026)

Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoning
di: Buehler, Markus J.
Pubblicazione: (2024)

Graph-Aware Isomorphic Attention for Adaptive Dynamics in Transformers
di: Buehler, Markus J.
Pubblicazione: (2025)

Self-Revising Discovery Systems for Science: A Categorical Framework for Agentic Artificial Intelligence
di: Wang, Fiona Y., et al.
Pubblicazione: (2026)

SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning
di: Ghafarollahi, Alireza, et al.
Pubblicazione: (2024)

PRefLexOR: Preference-based Recursive Language Modeling for Exploratory Optimization of Reasoning and Agentic Thinking
di: Buehler, Markus J.
Pubblicazione: (2024)

In-situ graph reasoning and knowledge expansion using Graph-PReFLexOR
di: Buehler, Markus J.
Pubblicazione: (2025)

Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities
di: Lu, Wei, et al.
Pubblicazione: (2024)

Autonomous Inorganic Materials Discovery via Multi-Agent Physics-Aware Scientific Reasoning
di: Ghafarollahi, Alireza, et al.
Pubblicazione: (2025)

Sparks: Multi-Agent Artificial Intelligence Model Discovers Protein Design Principles
di: Ghafarollahi, Alireza, et al.
Pubblicazione: (2025)

Blockwise Advantage Estimation for Multi-Objective RL with Verifiable Rewards
di: Pavlenko, Kirill, et al.
Pubblicazione: (2026)

Are LLMs Ready for Real-World Materials Discovery?
di: Miret, Santiago, et al.
Pubblicazione: (2024)

Generative Artificial Intelligence Extracts Structure-Function Relationships from Plants for New Materials
di: Luu, Rachel K., et al.
Pubblicazione: (2025)

RL Tango: Reinforcing Generator and Verifier Together for Language Reasoning
di: Zha, Kaiwen, et al.
Pubblicazione: (2025)

Aligning Reasoning LLMs for Materials Discovery with Physics-aware Rejection Sampling
di: Hyun, Lee, et al.
Pubblicazione: (2025)

Evaluating the Performance and Robustness of LLMs in Materials Science Q&A and Property Predictions
di: Wang, Hongchen, et al.
Pubblicazione: (2024)

FlowRL: Matching Reward Distributions for LLM Reasoning
di: Zhu, Xuekai, et al.
Pubblicazione: (2025)

REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards
di: Stojanovski, Zafir, et al.
Pubblicazione: (2025)

Mitigating Lost in Multi-turn Conversation via Curriculum RL with Verifiable Accuracy and Abstention Rewards
di: Li, Ming, et al.
Pubblicazione: (2025)

On Designing Effective RL Reward at Training Time for LLM Reasoning
di: Gao, Jiaxuan, et al.
Pubblicazione: (2024)

Matter-of-Fact: A Benchmark for Verifying the Feasibility of Literature-Supported Claims in Materials Science
di: Jansen, Peter, et al.
Pubblicazione: (2025)

Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
di: Ma, Zhengzhao, et al.
Pubblicazione: (2026)

X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Molecular Design
di: Buehler, Eric L., et al.
Pubblicazione: (2024)

Cephalo: Multi-Modal Vision-Language Models for Bio-Inspired Materials Analysis and Design
di: Buehler, Markus J.
Pubblicazione: (2024)

Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward
di: Wen, Xuexiang, et al.
Pubblicazione: (2026)

Rewarding Graph Reasoning Process makes LLMs more Generalized Reasoners
di: Peng, Miao, et al.
Pubblicazione: (2025)

LifeGPT: Topology-Agnostic Generative Pretrained Transformer Model for Cellular Automata
di: Berkovich, Jaime A., et al.
Pubblicazione: (2024)

A Relative-Budget Theory for Reinforcement Learning with Verifiable Rewards in Large Language Model Reasoning
di: Wachi, Akifumi, et al.
Pubblicazione: (2026)

AgentV-RL: Scaling Reward Modeling with Agentic Verifier
di: Zhang, Jiazheng, et al.
Pubblicazione: (2026)

Examining Reasoning LLMs-as-Judges in Non-Verifiable LLM Post-Training
di: Liu, Yixin, et al.
Pubblicazione: (2026)

Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Functional Materials Discovery
di: Rothfarb, Samuel, et al.
Pubblicazione: (2025)

Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs
di: Wen, Xumeng, et al.
Pubblicazione: (2025)

Language-Native Materials Processing Design by Lightly Structured Text Database and Reasoning Large Language Model
di: Liu, Yuze, et al.
Pubblicazione: (2025)

Beyond Outcome Verification: Verifiable Process Reward Models for Structured Reasoning
di: Pronesti, Massimiliano, et al.
Pubblicazione: (2026)

GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL
di: Yang, Rui, et al.
Pubblicazione: (2026)

CoVerRL: Breaking the Consensus Trap in Label-Free Reasoning via Generator-Verifier Co-Evolution
di: Pan, Teng, et al.
Pubblicazione: (2026)

Improving Neutral Point-of-View Generation with Data- and Parameter-Efficient RL
di: Hoffmann, Jessica, et al.
Pubblicazione: (2025)

ProofSketch: Efficient Verified Reasoning for Large Language Models
di: Sheshanarayana, Disha, et al.
Pubblicazione: (2025)