7 papers
Revisiting the Travel Planning Capabilities of Large Language Models
Bo-Wen Zhang, Jin Ye, Peng-Yu Hua +4
Travel planning serves as a critical task for long-horizon reasoning, exposing significant deficits in LLMs. However, existing benchmarks and evaluations primarily assess final pla…
Programmatic Context Augmentation for LLM-based Symbolic Regression
Hao Liu, Xiao-Wen Yang, Atharva Sehgal +4
Symbolic regression (SR), the task of discovering mathematical expressions that best describe a given dataset, remains a fundamental challenge in scientific discovery. Traditional…
Lifting Traces to Logic: Programmatic Skill Induction with Neuro-Symbolic Learning for Long-Horizon Agentic Tasks
Jie-Jing Shao, Haiyan Yin, Yueming Lyu +5
Foundation model-driven agents often struggle with long-horizon planning due to the transient nature of purely prompting-based reasoning. While existing skill induction methods mit…
Aligning Progress and Feasibility: A Neuro-Symbolic Dual Memory Framework for Long-Horizon LLM Agents
Bin Wen, Ruoxuan Zhang, Yang Chen +2
Large language models (LLMs) have demonstrated strong potential in long-horizon decision-making tasks, such as embodied manipulation and web interaction. However, agents frequently…
Thinking with Tables: Enhancing Multi-Modal Tabular Understanding via Neuro-Symbolic Reasoning
Kun-Yang Yu, Zhi Zhou, Shi-Yu Tian +6
Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities across modalities such as images and text. However, tabular data, despite being a criti…
Hindsight Credit Assignment for Long-Horizon LLM Agents
Hui-Ze Tan, Xiao-Wen Yang, Hao Chen +7
Large Language Model (LLM) agents often face significant credit assignment challenges in long-horizon, multi-step tasks due to sparse rewards. Existing value-free methods, such as…