# TReMu: Towards Neuro-Symbolic Temporal Reasoning for LLM-Agents with Memory in Multi-Session Dialogues

arXiv: https://arxiv.org/abs/2502.01630 · HTML: https://mlsanity.com/paper/2502.01630/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning.
- Builds on 4 of its 33 references that are in the map.
- First posted on arXiv 3 Feb 2025.

## Placed in

- LLM reasoning / [Knowledge- and tool-augmented reasoning](https://mlsanity.com/lr/knowledge-and-tool-augmented-reasoning/)
- LLM agents and tool use / [Agent memory systems](https://mlsanity.com/agents/agent-memory-systems/)

## Builds on (most cited first, 4 of 4)

- [MemGPT: Towards LLMs as Operating Systems](https://mlsanity.com/paper/2310.08560/) (2023)
- [FOLIO: Natural Language Reasoning with First-Order Logic](https://mlsanity.com/paper/2209.00840/) (2022)
- [SCM: Enhancing Large Language Model with Self-Controlled Memory Framework](https://mlsanity.com/paper/2304.13343/) (2023)
- [MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation](https://mlsanity.com/paper/2308.08239/) (2023)

## Built on by (most cited first, 25 of 25)

- [MemInsight: Autonomous Memory Augmentation for LLM Agents](https://mlsanity.com/paper/2503.21760/) (2025)
- [Rethinking Memory in LLM based Agents: Representations, Operations, and Emerging Topics](https://mlsanity.com/paper/2505.00675/) (2025)
- [Graph-based Agent Memory: Taxonomy, Techniques, and Applications](https://mlsanity.com/paper/2602.05665/) (2026)
- [REMem: Reasoning with Episodic Memory in Language Agent](https://mlsanity.com/paper/2602.13530/) (2026)
- [Pre-Storage Reasoning for Episodic Memory: Shifting Inference Burden to Memory for Personalized Dialogue](https://mlsanity.com/paper/2509.10852/) (2025)
- [SAMULE: Self-Learning Agents Enhanced by Multi-level Reflection](https://mlsanity.com/paper/2509.20562/) (2025)
- [It's High Time: A Survey of Temporal Question Answering](https://mlsanity.com/paper/2505.20243/) (2025)
- [Memory-T1: Reinforcement Learning for Temporal Reasoning in Multi-session Agents](https://mlsanity.com/paper/2512.20092/) (2025)
- [Your LLM Agents are Temporally Blind: The Misalignment Between Tool Use Decisions and Human Time Perception](https://mlsanity.com/paper/2510.23853/) (2025)
- [Memory in Large Language Models: Mechanisms, Evaluation and Evolution](https://mlsanity.com/paper/2509.18868/) (2025)
- [Optimizing LLM-Based Multi-Agent System with Textual Feedback: A Case Study on Software Development](https://mlsanity.com/paper/2505.16086/) (2025)
- [A Framework for Longitudinal Health AI Agents](https://mlsanity.com/paper/2604.12019/) (2026)
- [MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing](https://mlsanity.com/paper/2605.23986/) (2026)
- [EviMem: Evidence-Gap-Driven Iterative Retrieval for Long-Term Conversational Memory](https://mlsanity.com/paper/2604.27695/) (2026)
- [Momento: Evaluating Persistent Memory and Reasoning with Multi-Session Agentic Conversations](https://mlsanity.com/paper/2606.00832/) (2026)
- [STAR: Failure-Aware Markovian Routing for Multi-Agent Spatiotemporal Reasoning](https://mlsanity.com/paper/2605.10057/) (2026)
- [Memory Control Signals Emerge Before Action in Long Horizon Agents](https://mlsanity.com/paper/2609.27286/) (2026)
- [SPAN: Benchmarking and Improving Cross-Calendar Temporal Reasoning of Large Language Models](https://mlsanity.com/paper/2511.09993/) (2025)
- [Listening Alone, Understanding Together: Collaborative Context Recovery for Privacy-Aware AI](https://mlsanity.com/paper/2604.13348/) (2026)
- [LiFT: How to Enable In-Context Learning for Longitudinal Modelling](https://mlsanity.com/paper/2604.16382/) (2026)
- [The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes](https://mlsanity.com/paper/2606.11470/) (2026)
- [MemArena: An Ego-Centric Benchmark for On-Device Agentic Personal Memory Assistants at Scale](https://mlsanity.com/paper/2608.02613/) (2026)
- [ECHO: A Cognitively Inspired, Auditable Memory Plane for Long-Horizon Agents](https://mlsanity.com/paper/2608.21755/) (2026)
- [MemCodex: Self-Programming Hierarchical Memory for Language Agents](https://mlsanity.com/paper/2609.39765/) (2026)
- [AgentTime: Can Agents Estimate and Control Their Own Runtime?](https://mlsanity.com/paper/2610.09944/) (2026)

## Abstract (arXiv)

Temporal reasoning in multi-session dialogues presents a significant challenge which has been under-studied in previous temporal reasoning benchmarks. To bridge this gap, we propose a new evaluation task for temporal reasoning in multi-session dialogues and introduce an approach to construct a new benchmark by augmenting dialogues from LoCoMo and creating multi-choice QAs. Furthermore, we present TReMu, a new framework aimed at enhancing the temporal reasoning capabilities of LLM-agents in this context. Specifically, the framework employs time-aware memorization through timeline summarization, generating retrievable memory by summarizing events in each dialogue session with their inferred dates. Additionally, we integrate neuro-symbolic temporal reasoning, where LLMs generate Python code to perform temporal calculations and select answers. Experimental evaluations on popular LLMs demonstrate that our benchmark is challenging, and the proposed framework significantly improves temporal reasoning performance compared to baseline methods, raising from 29.83 on GPT-4o via standard prompting to 77.67 via our approach and highlighting its effectiveness in addressing temporal reasoning in multi-session dialogues.