No Universal Prompt: Unifying Reasoning through Adaptive Prompting for Temporal Table Reasoning

ACL ARR 2025 July Submission1347 Authors

Abstract: Temporal Table Reasoning is a critical challenge for Large Language Models (LLMs), requiring effective reasoning to extract relevant insights. Despite existence of multiple prompting methods, their impact on table reasoning remains largely unexplored. Furthermore, model performance varies drastically across different table and context structures, making it difficult to determine an optimal approach. This work investigates multiple prompting technique on diverse table types to determine that performance depends on factors such as entity type, table structure, requirement of additional context and question complexity, with "NO" single method consistently outperforming others. To address this, we introduce SEAR, an adaptive prompting framework inspired by human reasoning that dynamically adjusts to context and integrates structured reasoning. Our results demonstrate that SEAR achieves superior performance across all table types compared to baseline prompting techniques. Additionally, we explore the impact of table structure refactoring, finding that a unified representation enhances model reasoning.

Paper Type: Long

Research Area: Question Answering

Research Area Keywords: table QA, temporal reasoning, indirect supervision, LLM prompting, auxiliary data, logical reasoning

Contribution Types: Model analysis & interpretability, NLP engineering experiment, Data resources, Data analysis

Languages Studied: English

Previous URL: https://openreview.net/forum?id=kHVjSnvZts

Reassignment Request Area Chair: No, I want the same area chair from our previous submission (subject to their availability).

Reassignment Request Reviewers: No, I want the same set of reviewers from our previous submission (subject to their availability)

A1 Limitations Section: This paper has a limitations section.

A2 Potential Risks: N/A

B Use Or Create Scientific Artifacts: Yes

B1 Cite Creators Of Artifacts: Yes

B1 Elaboration: In Appendix E

B2 Discuss The License For Artifacts: N/A

B3 Artifact Use Consistent With Intended Use: N/A

B4 Data Contains Personally Identifying Info Or Offensive Content: N/A

B5 Documentation Of Artifacts: N/A

B6 Statistics For Data: Yes

B6 Elaboration: Added in Table 3

C Computational Experiments: Yes

C1 Model Size And Budget: Yes

C1 Elaboration: Experimental Setup, section 4

C2 Experimental Setup And Hyperparameters: Yes

C2 Elaboration: Experimental Setup, section 4

C3 Descriptive Statistics: Yes

C3 Elaboration: Result and Analysis, section 5

C4 Parameters For Packages: N/A

D Human Subjects Including Annotators: No

D1 Instructions Given To Participants: N/A

D2 Recruitment And Payment: N/A

D3 Data Consent: N/A

D4 Ethics Review Board Approval: N/A

D5 Characteristics Of Annotators: N/A

E Ai Assistants In Research Or Writing: Yes

E1 Information About Use Of Ai Assistants: Yes

E1 Elaboration: Ethics Statement: GPT 4 only used as a writing assistant

Author Submission Checklist: yes

Submission Number: 1347