Session-Based Recommendations

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

7 leaderboard tables shown for this task, 7 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 84 papers with code (172 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.

• Xception: Deep Learning with Depthwise Separable Convolutions
  7 Oct 2016 41 repositories listed Syntology ran 1 of 15 samples · 14 unverified
  We present an interpretation of Inception modules in convolutional neural networks as being an intermediate step in-between regular convolution and the depthwise separable convolution operation (a depthwise convolution…
• Session-based Recommendations with Recurrent Neural Networks
  21 Nov 2015 25 repositories listed Syntology ran 2 of 15 samples · 13 unverified · 4 pointer-only (licence)
  We apply recurrent neural networks (RNN) on a new domain, namely recommender systems.
• Recurrent Neural Networks with Top-k Gains for Session-based Recommendations
  12 Jun 2017 12 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  RNNs have been shown to be excellent models for sequential data and in particular for data that is generated by users in an session-based manner.
• Session-based Recommendation with Graph Neural Networks
  1 Nov 2018 8 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  To obtain accurate item embedding and take complex transitions of items into account, we propose a novel method, i.
• Session-aware Linear Item-Item Models for Session-based Recommendation
  30 Mar 2021 3 repositories listed
  Session-based recommendation aims at predicting the next item given a sequence of previous items consumed in the session, e.
• Personalized Graph Neural Networks with Attention Mechanism for Session-Aware Recommendation
  20 Oct 2019 3 repositories listed
  The other is Dot-Product Attention mechanism, which draws on the Transformer net to explicitly model the effect of historical sessions on the current session.
• News Session-Based Recommendations using Deep Neural Networks
  31 Jul 2018 3 repositories listed
  This architecture is composed of two modules, the first responsible to learn news articles representations, based on their text and metadata, and the second module aimed to provide session-based recommendations using…
• Evaluation of Session-based Recommendation Algorithms
  26 Mar 2018 3 repositories listed
  In many real-world applications, however, such long-term profiles often do not exist and recommendations therefore have to be made solely based on the observed behavior of a user during an ongoing session.
• Neural Attentive Session-based Recommendation
  13 Nov 2017 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Specifically, we explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session…
• Self-Supervised Graph Co-Training for Session-based Recommendation
  24 Aug 2021 2 repositories listed
  In this paper, for informative session-based data augmentation, we combine self-supervised learning with co-training, and then develop a framework to enhance session-based recommendation.
• Global Context Enhanced Graph Neural Networks for Session-based Recommendation
  9 Jun 2021 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  In GCE-GNN, we propose a novel global-level item representation learning layer, which employs a session-aware attention mechanism to recursively incorporate the neighbors' embeddings of each node on the global graph.
• Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation
  12 Dec 2020 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  Moreover, to enhance hypergraph modeling, we devise another graph convolutional network which is based on the line graph of the hypergraph and then integrate self-supervised learning into the training of the networks by…
• An efficient manifold density estimator for all recommendation systems
  2 Jun 2020 2 repositories listed
  Many unsupervised representation learning methods belong to the class of similarity learning models.
• Modeling Personalized Item Frequency Information for Next-basket Recommendation
  31 May 2020 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified
  NBR is in general more complex than the widely studied sequential (session-based) recommendation which recommends the next item based on a sequence of items.
• NISER: Normalized Item and Session Representations to Handle Popularity Bias
  10 Sep 2019 2 repositories listed
  The models using normalized item and session-graph representations perform significantly better: i.
• On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems
  12 Jul 2019 2 repositories listed Syntology ran 0 of 26 samples · 26 unverified
  A particular problem in that context is that online readers are often anonymous, which means that this personalization can only be based on the last few recorded interactions with the user, a setting named session-based…
• Contextual Hybrid Session-based News Recommendation with Recurrent Neural Networks
  15 Apr 2019 2 repositories listed Syntology ran 0 of 13 samples · 13 unverified
  The recommendation of news is often considered to be challenging, since the relevance of an article for a user can depend on a variety of factors, including the user's short-term reading interests, the reader's context,…
• Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks
  13 Jun 2017 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Session-based recommendations are highly relevant in many modern on-line services (e.
• Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based Recommendation
  7 Jul 2025 1 repository listed
  Session-based Recommendation (SBR) aims to predict the next item a user will likely engage with, using their interaction sequence within an anonymous session.
• Rethinking Contrastive Learning in Session-based Recommendation
  5 Jun 2025 1 repository listed
  Session-based recommendation aims to predict intents of anonymous users based on limited behaviors.
• Linear Item-Item Model with Neural Knowledge for Session-based Recommendation
  21 Apr 2025 1 repository listed
  Session-based recommendation (SBR) aims to predict users' subsequent actions by modeling short-term interactions within sessions.
• Unsupervised Graph Embeddings for Session-based Recommendation with Item Features
  19 Feb 2025 1 repository listed
  State-of-the-art sequential recommendation algorithms either use graph neural networks to model sessions in a graph or leverage the similarity of sessions by exploiting item features.
• SPGL: Enhancing Session-based Recommendation with Single Positive Graph Learning
  16 Dec 2024 1 repository listed
  It also takes into account the reverse positional information of items when constructing session representations to incorporate temporal information.
• Multi-Graph Co-Training for Capturing User Intent in Session-based Recommendation
  15 Dec 2024 1 repository listed
  Session-based recommendation focuses on predicting the next item a user will interact with based on sequences of anonymous user sessions.
• Enhancing Attributed Graph Networks with Alignment and Uniformity Constraints for Session-based Recommendation
  14 Oct 2024 1 repository listed
  In this paper, we propose a model-agnostic framework, named AttrGAU (Attributed Graph Networks with Alignment and Uniformity Constraints), to bring the MIA's superiority into existing attribute-agnostic models, to…
• Enhancing Sequential Music Recommendation with Negative Feedback-informed Contrastive Learning
  11 Sep 2024 1 repository listed
  Modern music streaming services are heavily based on recommendation engines to serve content to users.
• Multi-intent-aware Session-based Recommendation
  2 May 2024 1 repository listed Syntology ran 5 of 7 samples · 2 unverified · 7 pointer-only (licence)
  Session-based recommendation (SBR) aims to predict the following item a user will interact with during an ongoing session.
• Disentangling ID and Modality Effects for Session-based Recommendation
  19 Apr 2024 1 repository listed
  At the item level, we introduce a co-occurrence representation schema to explicitly incorporate cooccurrence patterns into ID representations.
• A Simple Yet Effective Approach for Diversified Session-Based Recommendation
  30 Mar 2024 1 repository listed
  It consists of two novel designs: a model-agnostic diversity-oriented loss function, and a non-invasive category-aware attention mechanism.
• Multi-view Intent Learning and Alignment with Large Language Models for Session-based Recommendation
  21 Feb 2024 1 repository listed
  To address the above challenges, we propose an LLM-enhanced SBR framework that integrates semantic and behavioral signals from multiple views.

Syntology lines on 12 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.