mlsanityData to 7 Oct 2026

Temporal Knowledge Question Answering via Abstract Reasoning Induction

arXiv 2311.09149 ↗First posted 15 Nov 2023cs.CL cs.AIcited by 23

On the map: LLM reasoning → Knowledge- and tool-augmented reasoning

Abstract (arXiv)

In this study, we address the challenge of enhancing temporal knowledge reasoning in Large Language Models (LLMs). LLMs often struggle with this task, leading to the generation of inaccurate or misleading responses. This issue mainly arises from their limited ability to handle evolving factual knowledge and complex temporal logic. To overcome these limitations, we propose Abstract Reasoning Induction (ARI) framework, which divides temporal reasoning into two distinct phases: Knowledge-agnostic and Knowledge-based. This framework offers factual knowledge support to LLMs while minimizing the incorporation of extraneous noisy data. Concurrently, informed by the principles of constructivism, ARI provides LLMs the capability to engage in proactive, self-directed learning from both correct and incorrect historical reasoning samples. By teaching LLMs to actively construct knowledge and methods, it can significantly boosting their temporal reasoning abilities. Our approach achieves remarkable improvements, with relative gains of 29.7% and 9.27% on two temporal QA datasets, underscoring its efficacy in advancing temporal reasoning in LLMs. The code can be found at https://github.com/czy1999/ARI-QA

Key facts. Cited by 23 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 4 of its 53 references that are in the map. First posted on arXiv 15 Nov 2023.

Builds on

4 of 53 references.

References · 4

  1. 2022A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodalcited by 106
  2. 2023Learning From Mistakes Makes LLM Better Reasonercited by 97
  3. 2023Large Language Models Are Semi-Parametric Reinforcement Learning Agentscited by 42
  4. 2023LMEye: An Interactive Perception Network for Large Language Modelscited by 27

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 6; 2025: 8; 2026: 9.

23 papers.

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  1. 2024Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Modelscited by 18
  2. 2024Temporal Knowledge Graph Question Answering: A Surveycited by 9
  3. 2025DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoningcited by 8
  4. 2025A Review of Incorporating Psychological Theories in LLMscited by 5
  5. 2025Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learningcited by 5
  6. 2026Temp-R1: A Unified Autonomous Agent for Complex Temporal KGQA via Reverse Curriculum Reinforcement Learningcited by 5
  7. 2026When Silence Is Golden: Can LLMs Learn to Abstain in Temporal QA and Beyond?cited by 5
  8. 2024A Multimodal In-Context Tuning Approach for E-Commerce Product Description Generationcited by 4
  9. 2025Reading Between the Timelines: RAG for Answering Diachronic Questionscited by 4
  10. 2024Cognitive Visual-Language Mapper: Advancing Multimodal Comprehension with Enhanced Visual Knowledge Alignmentcited by 3
  11. 2024Combining LLMs and Knowledge Graphs to Reduce Hallucinations in Question Answeringcited by 3
  12. 2025On the Temporal Question-Answering Capabilities of Large Language Models Over Anonymized Datacited by 2
11 more
  1. 2025Modeling the Diachronic Evolution of Legal Norms: An LRMoo-Based, Component-Level, Event-Centric Approach to Legal Knowledge Graphscited by 2
  2. 2025Plan of Knowledge: Retrieval-Augmented Large Language Models for Temporal Knowledge Graph Question Answeringcited by 2
  3. 2026Large Language Models Lack Temporal Awareness of Medical Knowledgecited by 2
  4. 2024Does the Generator Mind its Contexts? An Analysis of Generative Model Faithfulness under Context Transfercited by 1
  5. 2025A Question Answering Dataset for Temporal-Sensitive Retrieval-Augmented Generationcited by 0
  6. 2026Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledgecited by 0
  7. 2026Let the Agent Search: Autonomous Exploration Beats Rigid Workflows in Temporal Question Answeringcited by 0
  8. 2026Strategy-Induct: Task-Level Strategy Induction for Instruction Generationcited by 0
  9. 2026PulseCX: Breaking the Closed-World Assumption in Real-Time CXcited by 0
  10. 2026SABET-QA: Temporal Knowledge Graph Question Answeringcited by 0
  11. 2026SCoP: Structured Constraint Parsing for Evidence-Space Control in Temporal Knowledge Graph Question Answeringcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026AdapTime: Enabling Adaptive Temporal Reasoning in Large Language Models
  2. 2023Unlocking Temporal Question Answering for Large Language Models with Tailor-Made Reasoning Logic
  3. 2023Towards Robust Temporal Reasoning of Large Language Models via a Multi-Hop QA Dataset and Pseudo-Instruction Tuning
  4. 2023Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models
  5. 2024Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning
  6. 2025Question Answering under Temporal Conflict: Evaluating and Organizing Evolving Knowledge with LLMs
  7. 2024Enhancing Temporal Understanding in LLMs for Semi-structured Tables
  8. 2024Living in the Moment: Can Large Language Models Grasp Co-Temporal Reasoning?