Interactive Recommendation

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Most implemented papers archive 2025-07-28

10 shown of 10 papers with code (40 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation
  10 Jul 2023 2 repositories listed Syntology ran 3 of 9 samples · 6 unverified
  Through theoretical analyses, we find that the conservatism of existing methods fails in pursuing users' long-term satisfaction.
• Thought-Augmented Planning for LLM-Powered Interactive Recommender Agent
  30 Jun 2025 1 repository listed
  Interactive recommendation is a typical information-seeking task that allows users to interactively express their needs through natural language and obtain personalized recommendations.
• Contrastive Representation for Interactive Recommendation
  24 Dec 2024 1 repository listed
  To tackle this problem, we propose Contrastive Representation for Interactive Recommendation (CRIR).
• KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos
  18 Aug 2022 1 repository listed
  To facilitate model learning, we further collect rich features of users and items as well as users' behavior history.
• Modelling Users with Item Metadata for Explainable and Interactive Recommendation
  1 Jul 2022 1 repository listed
  The more interpretable the profile and this "matching function" are, the easier it is to provide users with accurate and intuitive explanations, and also to let them interact with the system.
• CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System
  4 Apr 2022 1 repository listed Syntology ran 0 of 9 samples · 9 unverified
  The basic idea is to first learn a causal user model on historical data to capture the overexposure effect of items on user satisfaction.
• Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability
  30 Jun 2021 1 repository listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  In this work, we consider how preference models in interactive recommendation systems determine the availability of content and users' opportunities for discovery.
• A Text-based Deep Reinforcement Learning Framework for Interactive Recommendation
  14 Apr 2020 1 repository listed
  IRSs usually face the large discrete action space problem, which makes most of the existing RL-based recommendation methods inefficient.
• RecSim: A Configurable Simulation Platform for Recommender Systems
  11 Sep 2019 1 repository listed Syntology ran 1 of 4 samples · 3 unverified
  We propose RecSim, a configurable platform for authoring simulation environments for recommender systems (RSs) that naturally supports sequential interaction with users.
• Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU
  24 Jun 2019 1 repository listed
  A novel query-based interactive recommender system is proposed in this paper, where \textbf{personalized questions are accurately generated from millions of automatically constructed questions} in Step 1, and…

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.