mlsanityData to 14 Oct 2026

MGFRec: Towards Reinforced Reasoning Recommendation with Multiple Groundings and Feedback

arXiv 2510.22888 ↗First posted 27 Oct 2025cs.IRcited by 1

On the map: LLM reasoning → LLM reasoning for recommendation

Abstract (arXiv)

The powerful reasoning and generative capabilities of large language models (LLMs) have inspired researchers to apply them to reasoning-based recommendation tasks, which require in-depth reasoning about user interests and the generation of recommended items. However, previous reasoning-based recommendation methods have typically performed inference within the language space alone, without incorporating the actual item space. This has led to over-interpreting user interests and deviating from real items. Towards this research gap, we propose performing multiple rounds of grounding during inference to help the LLM better understand the actual item space, which could ensure that its reasoning remains aligned with real items. Furthermore, we introduce a user agent that provides feedback during each grounding step, enabling the LLM to better recognize and adapt to user interests. Comprehensive experiments conducted on three Amazon review datasets demonstrate the effectiveness of incorporating multiple groundings and feedback. These findings underscore the critical importance of reasoning within the actual item space, rather than being confined to the language space, for recommendation tasks.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in LLM reasoning for recommendation, one of 17 directions in LLM reasoning. Builds on 23 of its 50 references that are in the map. First posted on arXiv 27 Oct 2025.

Builds on

23 of 50 references.

Closest ancestors · 6

Same direction, newest first

  1. 2025Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation5 Jun
  2. 2025Reinforced Latent Reasoning for LLM-based Recommendation25 May
  3. 2025R2ec: Towards Large Recommender Models with Reasoning22 May
  4. 2025Slow Thinking for Sequential Recommendation13 Apr
  5. 2025Reason4Rec: Deliberative User Preference Alignment of Large Language Models for Recommendation4 Feb
  6. 2023Enhancing Recommender Systems with Large Language Model Reasoning Graphs21 Aug

Other references · 17

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 9,379
  3. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  4. 2025Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learningcited by 1,444
  5. 2024OpenAI o1 System Cardcited by 1,244
  6. 2023Towards General Text Embeddings with Multi-stage Contrastive Learningcited by 723
  7. 2025VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Modelcited by 526
  8. 2025ReTool: Reinforcement Learning for Strategic Tool Use in LLMscited by 392
  9. 2025R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learningcited by 336
  10. 2025ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learningcited by 161
  11. 2025From LLM Reasoning to Autonomous AI Agents: A Comprehensive Reviewcited by 149
  12. 2025Towards General Agentic Intelligence via Environment Scalingcited by 54
5 more
  1. 2025Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendationcited by 51
  2. 2025Table-R1: Region-based Reinforcement Learning for Table Understandingcited by 37
  3. 2025Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learningcited by 33
  4. 2023RAH! RecSys-Assistant-Human: A Human-Centered Recommendation Framework with LLM Agentscited by 30
  5. 2025LARES: Latent Reasoning for Sequential Recommendationcited by 12

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026AgenticRec: A Recommendation-Oriented Agentic Framework with Progressive Tool-Integrated Reasoning Optimizationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Reinforced Preference Optimization for Reasoning-Augmented Recommendations
  2. 2026Reasoning to Rank: An End-to-End Solution for Exploiting Large Language Models for Recommendation
  3. 2024ReasoningRec: Bridging Personalized Recommendations and Human-Interpretable Explanations through LLM Reasoning
  4. 2025R4ec: A Reasoning, Reflection, and Refinement Framework for Recommendation Systems
  5. 2025OneRec-Think: In-Text Reasoning for Generative Recommendation
  6. 2025Generative Reasoning Recommendation via LLMs
  7. 2024Leveraging LLM Reasoning Enhances Personalized Recommender Systems
  8. 2026Implicit Reasoning for Large Language Model-based Generative Recommendation