Temporal Reasoning in Language Models

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Temporal reasoning asks whether language models can track when events happen, how states change, and which facts apply at a particular time. It matters for tasks such as answering questions about evolving knowledge, reconstructing long conversations, and interpreting clinical or legal timelines. Common approaches include temporal knowledge graphs and versioned memories, retrieval-augmented generation, executable rules for dates and intervals, and training or steering models to respect temporal cues. Benchmarks test date and event ordering, multi-turn memory, time-stamped evidence, and temporal patterns in video or time series; a central challenge is that retrieving a fact does not ensure the model knows whether it is current, historical, or valid for the question’s time frame.

Latest papers

99 papers27 papers in the last four weeks, up 93% on the four weeks before. 0.2% of all new papers.

TCC-RAG: Temporal Causal Chain-Guided RAG for Temporal Knowledge Graph Question Answering
Oct 28, 2026Xinxun Zhang, Yuxiang Wang, Shanshan Feng +6Knowledge Graph Question Answering Temporal Reasoning in Language Models
School of Computer Science, Wuhan University · Tencent Inc. · Hong Kong University of Science and Technology +1
From Document Layout to Causal Topology: An End-to-End Architecture for Temporal Causal Reasoning
Oct 25, 2026Zhifeng Yang, Wei Luo, Yongjian Chen +1Causal Reasoning in Language Models Temporal Reasoning in Language Models
School of Future Technology, South China University of Technology · Guangdong Artificial Intelligence and Digital Economy Laboratory (Guangzhou)
Collection-Date Assignment Redirects Answers in Temporal QA
Oct 23, 2026Minsu Oh, Seunghui Jwa, Soo Kyun Kim +1Temporal QA Temporal Reasoning in Language Models
Department of Artificial Intelligence, Jeju National University · Department of Computer Engineering, Jeju National University
Keeping Time vs. Understanding Time: Neither Alone Explains Temporal Reasoning in LLMs
Oct 21, 2026Auss Abbood, Fernando Martínez-Plumed, José Hernández-Orallo +1Temporal Reasoning in Language Models Temporal Reasoning
Language Technology Lab, University of Cambridge, UK · Valencian Research Institute for Artificial Intelligence (VRAIN) Universitat Politècnica de València, Spain · Leverhulme Centre for the Future of Intelligence, University of Cambridge, UK
Temporal Evidence-Parameter Co-Alignment for LLM Reasoning over Temporal Knowledge Graphs
Oct 20, 2026Jiapu WangTemporal Reasoning in Language Models Temporal KGs
School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, 210094, China
Where and Why Search-Augmented LLMs Fail When Reasoning over Rapidly Evolving Knowledge
Oct 18, 2026Tianyi Hu, Bhavyajeet Singh, Niket Tandon +1Retrieval-Augmented Reasoning LLM Reasoning
Aarhus University · Microsoft Research · Technische Universität Darmstadt
Beyond Large Language Models: A Mental World Model Framework for Mental Modeling, Simulation, Evolution, and Interpretability
Oct 16, 2026Qingshi Wang, Huiqi TongTheory of Mind Implicit Reasoning in Language Models
School of Computer Science, University of Bristol, Bristol, United Kingdom · Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, United States
Grid-Bench: Can LLMs Predict How Discrete Worlds Change?
Oct 15, 2026Zixiang Xu, Zirui Song, Wanrong Zheng +16Spatial Reasoning Benchmarks LLM Evaluation
University of Southern California · Mohamed bin Zayed University of Artificial Intelligence · Meta +3
TEM: Temporal State Tracking Memory for Large Language Model Agents
Oct 15, 2026Pengfeng Song, Yunkai Zhuang, Liye ShiLLM Agent Memory Memory-Augmented Language Model Agents
School of Information and Intelligent Engineering,Zhejiang Wanli University,Ningbo,315100,China.
Can LLMs Tell Stories Out of Order? A Corpus and Benchmark for Nonlinear Narrative Generation
Oct 15, 2026Syed Rifat Raiyan, Md. Tariquzzaman, Md Farhan Ishmam +1Narrative Generation Text Generation
Islamic University of Technology, Bangladesh · University of Utah, USA · University of Southern California, USA
ChronoCulture: Evaluating Cultural Awareness Across Time in Large Language Models
Oct 14, 2026Rusali Saha, Nitya Khurana, Ruihong Huang +1Cultural Knowledge in Language Models Cross-Cultural Language Model Evaluation
Texas A&M University
Fresh at Decision, Stale at Action: Routing New Information to LLM Decisions Already Made
Oct 13, 2026Ayoub Merimi, Souhail Bakkali, Abdeljalil SakatLLM Decision-Making Temporal Reasoning in Language Models
Evaluating Temporal Reasoning in Large Language Models: Event Temporal Relation Extraction with Allen's Interval Algebra, Logical Consistency, and Relative Time in Narratives
Oct 12, 2026Adib Sakhawat, Fardeen Sadab, Tamjid Hasan Fahim +9Temporal Reasoning in Language Models Relation Extraction
Islamic University of Technology, Gazipur, Bangladesh · Rajshahi University of Engineering & Technology, Rajshahi, Bangladesh
Engram Injection: A Study of Temporal Validity in Parametric Language-Model Memory
Oct 11, 2026Sam Siavoshian, Omar Ramadan, Amir K. Saeed +2Temporal Reasoning in Language Models Persistent Memory for Language Models
GesBench: When and Where Do Multimodal Language Models Perceive Social Meaning?
Oct 10, 2026Zonghuan Li, Hayley Hung, Chirag RamanMultimodal Model Evaluation Multimodal Understanding
Department of EEMCS, Delft University of Technology, Delft, Netherlands
TLA-Verus: Generating and Solving Temporal Proof Obligations with LLM Agents
Oct 10, 2026Kseniia Strelbytska, Balázs Szilágyi, Anna Mészáros +1Formal Verification Automated Theorem Proving
Stephen Perse Cambridge, UK · University of Cambridge, UK · Reasonable
SciTBERT: A family of chronologically consistent language models for scientific and technological language processing
Oct 8, 2026Thomas Gebhart, Russell J. FunkLanguage Modeling Text Embedding Models
Carlson School of Management, University of Minnesota
Is the Future Predictable? Modeling Future Predictability for Reliable Temporal Reasoning
Oct 8, 2026Yongyi Huang, Huaping Zhang, Wenyao Cui +3Temporal Reasoning in Language Models LLM Reliability
Beijing Institute of Technology · Zhongguancun Academy
Lapras: Latent Reasoning for Time Series Language Models
Oct 8, 2026Yuliang Chen, Yu Yvonne Wu, Patrick Langer +11Time Series Language Modeling Temporal Reasoning in Language Models
Dartmouth College · Aionic Labs · Agentic Systems Lab, ETH Zurich +2
Learning Situation-Conditioned Thinking Policies for Long-Term LLM Agents
Oct 7, 2026Hong SuLLM Agent Memory Long-Horizon LLM Agents
School of Computer Science, Chengdu University of Information Technology, Chengdu, China
TrajLong: Co-Designing Agentic and Long-Context Supervision for Mid-Training
Oct 4, 2026Miao Peng, Qintong Zhang, Nuo Chen +8LLM Agent Training Long-Context Language Modeling
The Hong Kong University of Science and Technology (Guangzhou) · Hunyuan Team, Tencent · Peking University
Evaluating Multi-Dimensional Generalization of Large Language Models in Temporal Extraction Tasks
Oct 1, 2026Fahmid Shahriar Iqbal, Ritam Dutt, Soumitra Das +2Language Model Generalization Temporal Reasoning in Language Models
University of North Texas · Carnegie Mellon University · University of Massachusetts Amherst +1
A rubric landscape for evaluating clinical reasoning in large language models: what exists, what is missing, and what needs to be combined
Oct 1, 2026Zhangshu Joshua Jiang, Zina Ibrahim, James T. TeoFaithfulness of Language Model Explanations Temporal Reasoning in Language Models
DRIVE-Health CDT Department of Biostatistics and Health Informatics Institute of Psychiatry, Psychology and Neuroscience King’s College London London, UK · Cleveland Clinic London London, UK
OpenTSLM TeeMoE: A Unified Time-Series Language Model for Forecasting, Contextual Prediction, and Reasoning
Sep 30, 2026Tony Chen, Timo Stoffregen, Maxwell Xu +8Temporal Reasoning in Language Models LLM-Based Time Series Forecasting
Columbia University, USA · Stanford University, USA · Aionic Labs, Switzerland +4
Reasoning Externalization for Faithful Large Language Model Narratives of Stock Return Predictions
Sep 30, 2026Sujung Kim, Seung Hwan Cho, Sangjin Park +1Numerical Reasoning in Language Models Faithfulness of Language Model Explanations
Department of Industrial Data Engineering, Hanyang University, Republic of Korea · School of Interdisciplinary Industrial Studies, Hanyang University, Republic of Korea
StateTree: Enhancing Long-Term Dialogue Reasoning via Reinforcement Learning
Sep 30, 2026Naen Xu, Wanqing Cui, Yibo Hu +5Temporal Reasoning in Language Models RL for Language Model Reasoning
Zhejiang University · Taobao & Tmall Group of Alibaba
Concept-Grounded Attention: A Controlled Evaluation of Graph-Injected Attention, Temporal Versioning, and Epistemic Status
Sep 30, 2026Sachin Dev Duggal, Pradyumna Swarnalatha Ramanna, Alexandros VassiliadesLLM Grounding Temporal Reasoning in Language Models
SeKondBrain AI Labs, London, United Kingdom.
Memory Consolidation Flattens the Temporal Shape of User Facts
Sep 29, 2026Sugam Panthi, Muhaiminul Yeamin, Siyan Luo +1Long-Term Conversational Memory Memory Consolidation
AIMS Lab, The University of Southern Mississippi
Identifying Temporal Features within Transcoders for Time Sensitive Factual Recall
Sep 27, 2026Sanjay Govindan, Yang Song, Maurice PagnuccoTemporal Reasoning in Language Models LLM Interpretability
University of New South Wales, Sydney
World Agent: Can Language Models Keep a World Running?
Sep 26, 2026Weixing Chen, Weipeng Zhang, Nan An +2World Model Evaluation World Models
Sun Yat-sen University · South China University of Technology · Guangdong Key Laboratory of Big Data Analysis and Processing +2

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TCC-RAG: Temporal Causal Chain-Guided RAG for Temporal Knowledge Graph Question Answering

Xinxun Zhang, Yuxiang Wang, Shanshan Feng, Jun Zhang+5

School of Computer Science, Wuhan University · Tencent Inc. · Hong Kong University of Science and Technology+1

Knowledge Graph Question Answering Temporal Reasoning in Language Models Temporal KGs Graph Retrieval-Augmented Generation Causal Reasoning in Language Models

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Recent advances in large language models (LLMs) have spurred growing interest in temporal knowledge graph question answering (TKGQA). Most existing methods rely on semantic retrieval augmented generation (RAG), which suffers from fundamental limitations in complex temporal reasoning. On the one hand, semantic-based RAG methods struggle to capture the multi-hop causal knowledge required for complex temporal reasoning. On the other hand, these methods introduce excessive redundant knowledge, trapping LLMs in spurious reasoning chains that potentially result in erroneous answers. To address these problems, we propose a Temporal Causal Chain-guided RAG (TCC-RAG) to retrieve a concise yet sufficient set of causal knowledge to support complex temporal reasoning. Specifically, we reformulate the temporal knowledge graph into a multi-view causal cue graph, with causal cues inducing connections that explicitly encode temporal evolution and causal dynamics. Based on the causal cue graph, we construct a query-specific temporal causal chain to guide the retrieval process, enabling the model to focus on a concise set of causally relevant knowledge. Finally, we introduce a causal evidence filter to refine the retrieved knowledge, ensuring its causal consistency with the underlying temporal logic of the query. Experiments show that TCC-RAG achieves substantial performance gains of 10.72% and 8.40% on two TKGQA benchmarks, and delivers a remarkable 62.97% improvement for multi-step temporal reasoning.