Enhancing Temporal Sensitivity and Reasoning for Time-Sensitive Question Answering
On the map: LLM reasoning → Knowledge- and tool-augmented reasoning
Abstract (arXiv)
Time-Sensitive Question Answering (TSQA) demands the effective utilization of specific temporal contexts, encompassing multiple time-evolving facts, to address time-sensitive questions. This necessitates not only the parsing of temporal information within questions but also the identification and understanding of time-evolving facts to generate accurate answers. However, current large language models still have limited sensitivity to temporal information and their inadequate temporal reasoning capabilities. In this paper, we propose a novel framework that enhances temporal awareness and reasoning through Temporal Information-Aware Embedding and Granular Contrastive Reinforcement Learning. Experimental results on four TSQA datasets demonstrate that our framework significantly outperforms existing LLMs in TSQA tasks, marking a step forward in bridging the performance gap between machine and human temporal understanding and reasoning.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 27 of its 33 references that are in the map. First posted on arXiv 25 Sep 2024.
Builds on
27 of 33 references.
References · 27
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15 more
- 2017SearchQA: A New Q&A Dataset Augmented with Context from a Search Enginecited by 221
- 2021A Dataset for Answering Time-Sensitive Questionscited by 150
- 2021SituatedQA: Incorporating Extra-Linguistic Contexts into QAcited by 145
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Built on by
Citing papers per year: 2025: 8; 2026: 1.
9 papers.
- 2025HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generationcited by 13
- 2025It's High Time: A Survey of Temporal Question Answeringcited by 12
- 2025RAG Meets Temporal Graphs: Time-Sensitive Modeling and Retrieval for Evolving Knowledgecited by 10
- 2025Nature's Insight: A Novel Framework and Comprehensive Analysis of Agentic Reasoning Through the Lens of Neurosciencecited by 3
- 2025DailyQA: A Benchmark to Evaluate Web Retrieval Augmented LLMs Based on Capturing Real-World Changescited by 3
- 2025Discrete Minds in a Continuous World: Do Language Models Know Time Passes?cited by 2
- 2025NeSTR: A Neuro-Symbolic Abductive Framework for Temporal Reasoning in Large Language Modelscited by 1
- 2026RAG-Enhanced Large Language Models for Dynamic Content Expiration Prediction in Web Searchcited by 1
- 2025MTPChat: A Multimodal Time-Aware Persona Dataset for Conversational Agentscited by 0
- 2026RAG-Enhanced Large Language Models for Dynamic Content Expiration Prediction in Web Search13 May 2026
- 2025NeSTR: A Neuro-Symbolic Abductive Framework for Temporal Reasoning in Large Language Models8 Dec 2025
- 2025RAG Meets Temporal Graphs: Time-Sensitive Modeling and Retrieval for Evolving Knowledge15 Oct 2025
- 2025Discrete Minds in a Continuous World: Do Language Models Know Time Passes?6 Jun 2025
- 2025It's High Time: A Survey of Temporal Question Answering26 May 2025
- 2025DailyQA: A Benchmark to Evaluate Web Retrieval Augmented LLMs Based on Capturing Real-World Changes22 May 2025
- 2025Nature's Insight: A Novel Framework and Comprehensive Analysis of Agentic Reasoning Through the Lens of Neuroscience7 May 2025
- 2025HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation3 Mar 2025
- 2025MTPChat: A Multimodal Time-Aware Persona Dataset for Conversational Agents9 Feb 2025
Similar, not cited
Close in wording, no citation either way
- 2024UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs' Memorization
- 2023Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models
- 2023Unlocking Temporal Question Answering for Large Language Models with Tailor-Made Reasoning Logic
- 2026TS-Skill: A Benchmark for Evaluating Analytical Skills in Time-Series Question Answering
- 2023Towards Robust Temporal Reasoning of Large Language Models via a Multi-Hop QA Dataset and Pseudo-Instruction Tuning
- 2023Fusing Temporal Graphs into Transformers for Time-Sensitive Question Answering
- 2025Plan of Knowledge: Retrieval-Augmented Large Language Models for Temporal Knowledge Graph Question Answering
- 2024Timo: Towards Better Temporal Reasoning for Language Models