mlsanityData to 7 Oct 2026

Living in the Moment: Can Large Language Models Grasp Co-Temporal Reasoning?

arXiv 2406.09072 ↗First posted 13 Jun 2024cs.CLcited by 25

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

Abstract (arXiv)

Temporal reasoning is fundamental for large language models (LLMs) to comprehend the world. Current temporal reasoning datasets are limited to questions about single or isolated events, falling short in mirroring the realistic temporal characteristics involving concurrent nature and intricate temporal interconnections. In this paper, we introduce CoTempQA, a comprehensive co-temporal Question Answering (QA) benchmark containing four co-temporal scenarios (Equal, Overlap, During, Mix) with 4,748 samples for evaluating the co-temporal comprehension and reasoning abilities of LLMs. Our extensive experiments reveal a significant gap between the performance of current LLMs and human-level reasoning on CoTempQA tasks. Even when enhanced with Chain of Thought (CoT) methodologies, models consistently struggle with our task. In our preliminary exploration, we discovered that mathematical reasoning plays a significant role in handling co-temporal events and proposed a strategy to boost LLMs' co-temporal reasoning from a mathematical perspective. We hope that our CoTempQA datasets will encourage further advancements in improving the co-temporal reasoning capabilities of LLMs. Our code is available at https://github.com/zhaochen0110/Cotempqa.

Key facts. Cited by 25 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 25 of its 54 references that are in the map. First posted on arXiv 13 Jun 2024.

Builds on

25 of 54 references.

Closest ancestors · 5

Same direction, newest first

  1. 2023TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models29 Nov
  2. 2023MenatQA: A New Dataset for Testing the Temporal Comprehension and Reasoning Abilities of Large Language Models8 Oct
  3. 2023Back to the Future: Towards Explainable Temporal Reasoning with Large Language Models2 Oct
  4. 2023TRAM: Benchmarking Temporal Reasoning for Large Language Models2 Oct
  5. 2023Unlocking Temporal Question Answering for Large Language Models with Tailor-Made Reasoning Logic24 May

Other references · 20

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  3. 2023A Survey of Large Language Modelscited by 2,537
  4. 2023Code Llama: Open Foundation Models for Codecited by 2,105
  5. 2023GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpointscited by 1,311
  6. 2023A Survey on Evaluation of Large Language Modelscited by 1,227
  7. 2023WizardLM: Empowering large pre-trained language models to follow complex instructionscited by 1,116
  8. 2023Multimodal Chain-of-Thought Reasoning in Language Modelscited by 740
  9. 2023WizardCoder: Empowering Code Large Language Models with Evol-Instructcited by 728
  10. 2022PAL: Program-aided Language Modelscited by 635
  11. 2023WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instructcited by 618
  12. 2022Towards Reasoning in Large Language Models: A Surveycited by 593
8 more
  1. 2022RealTime QA: What's the Answer Right Now?cited by 239
  2. 2022A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodalcited by 106
  3. 2024Can AI Assistants Know What They Don't Know?cited by 47
  4. 2022RoMQA: A Benchmark for Robust, Multi-evidence, Multi-answer Question Answeringcited by 19
  5. 2023Question Answering as Programming for Solving Time-Sensitive Questionscited by 14
  6. 2023GLoRE: Evaluating Logical Reasoning of Large Language Modelscited by 13
  7. 2022Delving Deep into Regularity: A Simple but Effective Method for Chinese Named Entity Recognitioncited by 7
  8. 2024Joint Multi-Facts Reasoning Network For Complex Temporal Question Answering Over Knowledge Graphcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 7; 2025: 14; 2026: 4.

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  1. 2025OpenThinkIMG: Learning to Think with Images via Visual Tool Reinforcement Learningcited by 163
  2. 2025A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyondcited by 131
  3. 2024LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-trainingcited by 122
  4. 2024Twin-Merging: Dynamic Integration of Modular Expertise in Model Mergingcited by 114
  5. 2025PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Modelscited by 98
  6. 2024Timo: Towards Better Temporal Reasoning for Language Modelscited by 21
  7. 2026Large Language Model Reasoning Failurescited by 20
  8. 2024UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs' Memorizationcited by 17
  9. 2025It's High Time: A Survey of Temporal Question Answeringcited by 12
  10. 2024SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Informationcited by 11
  11. 2025Do Cognitively Interpretable Reasoning Traces Improve LLM Performance?cited by 11
  12. 2024On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusioncited by 9
13 more
  1. 2025From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibrationcited by 8
  2. 2025Interpretable Traces, Unexpected Outcomes: Investigating the Disconnect in Trace-Based Knowledge Distillationcited by 8
  3. 2025ExAnte: A Benchmark for Ex-Ante Inference in Large Language Modelscited by 5
  4. 2025Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applicationscited by 4
  5. 2024Mitigating Multilingual Hallucination in Large Vision-Language Modelscited by 3
  6. 2025TRAVELER: A Benchmark for Evaluating Temporal Reasoning across Vague, Implicit and Explicit Referencescited by 3
  7. 2025How GPT learns layer by layercited by 2
  8. 2025Factual Knowledge in Language Models: Robustness and Anomalies under Simple Temporal Context Variationscited by 1
  9. 2025AgentCaster: Reasoning-Guided Tornado Forecastingcited by 1
  10. 2026RAG-Enhanced Large Language Models for Dynamic Content Expiration Prediction in Web Searchcited by 1
  11. 2025MIN-Merging: Merge the Important Neurons for Model Mergingcited by 0
  12. 2026Teaching Large Language Models When Not to Know: Learning Temporal Critique for Ex-Ante Reasoningcited by 0
  13. 2026The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modescited by 0

Similar, not cited

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  1. 2025TIME: A Multi-level Benchmark for Temporal Reasoning of LLMs in Real-World Scenarios
  2. 2024Test of Time: A Benchmark for Evaluating LLMs on Temporal Reasoning
  3. 2025ChronoSense: Exploring Temporal Understanding in Large Language Models with Time Intervals of Events
  4. 2026AdapTime: Enabling Adaptive Temporal Reasoning in Large Language Models
  5. 2025TransientTables: Evaluating LLMs' Reasoning on Temporally Evolving Semi-structured Tables
  6. 2024Time Awareness in Large Language Models: Benchmarking Fact Recall Across Time
  7. 2024Enhancing Temporal Understanding in LLMs for Semi-structured Tables
  8. 2025A Study into Investigating Temporal Robustness of LLMs