mlsanityData to 14 Oct 2026

ReTrace: Interactive Visualizations for Reasoning Traces of Large Reasoning Models

arXiv 2511.11187 ↗First posted 14 Nov 2025cs.HCcited by 3

On the map: LLM reasoning → Reasoning benchmarks and evaluation

Abstract (arXiv)

Recent advances in Large Language Models have led to Large Reasoning Models, which produce step-by-step reasoning traces. These traces offer insight into how models think and their goals, improving explainability and helping users follow the logic, learn the process, and even debug errors. These traces, however, are often verbose and complex, making them cognitively demanding to comprehend. We address this challenge with ReTrace, an interactive system that structures and visualizes textual reasoning traces to support understanding. We use a validated reasoning taxonomy to produce structured reasoning data and investigate two types of interactive visualizations thereof. In a controlled user study, both visualizations enabled users to comprehend the model's reasoning more accurately and with less perceived effort than a raw text baseline. The results of this study could have design implications for making long and complex machine-generated reasoning processes more usable and transparent, an important step in AI explainability.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning. Builds on 28 of its 75 references that are in the map. First posted on arXiv 14 Nov 2025.

Builds on

28 of 75 references.

Closest ancestors · 9

Same direction, newest first

  1. 2025Qwen3 Technical Report14 May
  2. 2025Beyond the Last Answer: Your Reasoning Trace Uncovers More than You Think29 Apr
  3. 2025DeepSeek-R1 Thoughtology: Let's think about LLM Reasoning2 Apr
  4. 2025Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models28 Mar
  5. 2025ReasonGraph: Visualisation of Reasoning Paths6 Mar
  6. 2025LLM Post-Training: A Deep Dive into Reasoning Large Language Models28 Feb
  7. 2025ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning3 Feb
  8. 2023Natural Language Reasoning, A Survey26 Mar
  9. 2022Towards Reasoning in Large Language Models: A Survey20 Dec

Other references · 19

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2021Training Verifiers to Solve Math Word Problemscited by 10,109
  3. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  4. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  5. 2025Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilitiescited by 3,796
  6. 2017Towards A Rigorous Science of Interpretable Machine Learningcited by 1,416
  7. 2025s1: Simple test-time scalingcited by 1,341
  8. 2024OpenAI o1 System Cardcited by 1,244
  9. 2022STaR: Bootstrapping Reasoning With Reasoningcited by 940
  10. 2019DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphscited by 903
  11. 2021Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigmcited by 606
  12. 2020Questioning the AI: Informing Design Practices for Explainable AI User Experiencescited by 253
7 more
  1. 2025Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safetycited by 249
  2. 2025ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learningcited by 192
  3. 2025The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Taskscited by 152
  4. 2023LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Modelscited by 82
  5. 2024Supporting Sensemaking of Large Language Model Outputs at Scalecited by 27
  6. 2021Principles of Explanation in Human-AI Systemscited by 25
  7. 2019Visualizing Attention in Transformer-Based Language Representation Modelscited by 8

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026TraceView: Interactive Visualization of Agentic Program Repair Trajectoriescited by 2
  2. 2026InconLens: Interactive Visual Diagnosis of Behavioral Inconsistencies in LLM-based Agentic Systemscited by 1
  3. 2026ReasoningLens: Hierarchical Visualization and Diagnostic Auditing for Large Reasoning Modelscited by 1

Similar, not cited

Close in wording, no citation either way

  1. 2025Interactive Reasoning: Visualizing and Controlling Chain-of-Thought Reasoning in Large Language Models
  2. 2026InSight: A Benchmark for Agentic Claim Verification in Interactive Visualizations
  3. 2025REMA: A Unified Reasoning Manifold Framework for Interpreting Large Language Model
  4. 2025RE-IMAGINE: Symbolic Benchmark Synthesis for Reasoning Evaluation
  5. 2025Beyond the Black Box: Demystifying Multi-Turn LLM Reasoning with VISTA
  6. 2026ReasoningFlow: Discourse Structures for Understanding LLM Reasoning Traces
  7. 2026Graphionale: How Graph Visualizations of LLM Rationales Affect Human Decision Making
  8. 2025When Visualizing is the First Step to Reasoning: MIRA, a Benchmark for Visual Chain-of-Thought