Imagen de Portada

ACPBench Hard: Unrestrained Reasoning about Action, Change, and Planning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Kokel, Harsha, Katz, Michael, Srinivas, Kavitha, Sohrabi, Shirin
Formato:	Preprint
Publicado:	2025
Materias:	Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

ACPBench: Reasoning about Action, Change, and Planning
por: Kokel, Harsha, et al.
Publicado: (2024)

Thought of Search: Planning with Language Models Through The Lens of Efficiency
por: Katz, Michael, et al.
Publicado: (2024)

Planning in the LLM Era: Building for Reliability and Efficiency
por: Katz, Michael, et al.
Publicado: (2026)

Learning and Reusing Policy Decompositions for Hierarchical Generalized Planning with LLM Agents
por: Sohrabi, Shirin, et al.
Publicado: (2026)

Automating Thought of Search: A Journey Towards Soundness and Completeness
por: Cao, Daniel, et al.
Publicado: (2024)

Large Language Models as Planning Domain Generators
por: Oswald, James, et al.
Publicado: (2024)

Model Space Reasoning as Search in Feedback Space for Planning Domain Generation
por: Oswald, James, et al.
Publicado: (2026)

Make Planning Research Rigorous Again!
por: Katz, Michael, et al.
Publicado: (2025)

QueryGym: Step-by-Step Interaction with Relational Databases
por: Ananthakrishnan, Haritha, et al.
Publicado: (2025)

Seemingly Simple Planning Problems are Computationally Challenging: The Countdown Game
por: Katz, Michael, et al.
Publicado: (2025)

Unifying and Certifying Top-Quality Planning
por: Katz, Michael, et al.
Publicado: (2024)

Some Orders Are Important: Partially Preserving Orders in Top-Quality Planning
por: Katz, Michael, et al.
Publicado: (2024)

Less is More: Learning Graph Tasks with Just LLMs
por: Shirai, Sola, et al.
Publicado: (2025)

Combining Planning and Reinforcement Learning for Solving Relational Multiagent Domains
por: Prabhakar, Nikhilesh, et al.
Publicado: (2025)

TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes
por: Khatiwada, Aamod, et al.
Publicado: (2024)

Can Cross Encoders Produce Useful Sentence Embeddings?
por: Ananthakrishnan, Haritha, et al.
Publicado: (2025)

ActionReasoningBench: Reasoning about Actions with and without Ramification Constraints
por: Handa, Divij, et al.
Publicado: (2024)

A Planning Compilation to Reason about Goal Achievement at Planning Time
por: Pozanco, Alberto, et al.
Publicado: (2025)

Can LLMs Fix Issues with Reasoning Models? Towards More Likely Models for AI Planning
por: Caglar, Turgay, et al.
Publicado: (2023)

MARBLE: A Hard Benchmark for Multimodal Spatial Reasoning and Planning
por: Jiang, Yulun, et al.
Publicado: (2025)

Answer Set Programming Modulo Theories and Reasoning about Continuous Changes
por: Lee, Joohyung, et al.
Publicado: (2025)

LLM+AL: Bridging Large Language Models and Action Languages for Complex Reasoning about Actions
por: Ishay, Adam, et al.
Publicado: (2025)

Can AI autonomously build, operate, and use the entire data stack?
por: Agarwal, Arvind, et al.
Publicado: (2025)

Plan Then Action:High-Level Planning Guidance Reinforcement Learning for LLM Reasoning
por: Dou, Zhihao, et al.
Publicado: (2025)

Reasoning About Action and Change
por: de Saint-Cyr, Florence Dupin, et al.
Publicado: (2024)

Interpretable Action Recognition on Hard to Classify Actions
por: Anichenko, Anastasia, et al.
Publicado: (2024)

Learning Type-Generalized Actions for Symbolic Planning
por: Tanneberg, Daniel, et al.
Publicado: (2023)

TOPJoin: A Context-Aware Multi-Criteria Approach for Joinable Column Search
por: Kokel, Harsha, et al.
Publicado: (2025)

Evaluating Joinable Column Discovery Approaches for Context-Aware Search
por: Kokel, Harsha, et al.
Publicado: (2025)

AI Planning: A Primer and Survey (Preliminary Report)
por: Chen, Dillon Z., et al.
Publicado: (2024)

ASTRA-bench: Evaluating Tool-Use Agent Reasoning and Action Planning with Personal User Context
por: Xiu, Zidi, et al.
Publicado: (2026)

ProRAC: A Neuro-symbolic Method for Reasoning about Actions with LLM-based Progression
por: Wu, Haoyong, et al.
Publicado: (2025)

Plan-MCTS: Plan Exploration for Action Exploitation in Web Navigation
por: Zhang, Weiming, et al.
Publicado: (2026)

On Computing Plans with Uniform Action Costs
por: Pozanco, Alberto, et al.
Publicado: (2024)

Can Reasoning Models Reason about Hardware? An Agentic HLS Perspective
por: Collini, Luca, et al.
Publicado: (2025)

Reasoning about unpredicted change and explicit time
por: de Saint-Cyr, Florence Dupin, et al.
Publicado: (2024)

NurseSchedRL: Attention-Guided Reinforcement Learning for Nurse-Patient Assignment
por: Koduri, Harsha
Publicado: (2025)

Out of style: Misadventures with LLMs and code style transfer
por: Munson, Karl, et al.
Publicado: (2024)

Counting and Reasoning with Plans
por: Speck, David, et al.
Publicado: (2025)

MiGrATe: Mixed-Policy GRPO for Adaptation at Test-Time
por: Phan, Peter, et al.
Publicado: (2025)