Citation Prediction

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

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

2 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.

Most implemented papers archive 2025-07-28

11 shown of 11 papers with code (24 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.

• SPECTER: Document-level Representation Learning using Citation-informed Transformers
  15 Apr 2020 5 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  We propose SPECTER, a new method to generate document-level embedding of scientific documents based on pretraining a Transformer language model on a powerful signal of document-level relatedness: the citation graph.
• BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
  17 Apr 2021 3 repositories listed Syntology ran 3 of 4 samples · 1 unverified
  To address this, and to facilitate researchers to broadly evaluate the effectiveness of their models, we introduce Benchmarking-IR (BEIR), a robust and heterogeneous evaluation benchmark for information retrieval.
• CiteBART: Learning to Generate Citations for Local Citation Recommendation
  23 Dec 2024 1 repository listed Syntology ran 0 of 16 samples · 16 unverified
  In the local context-only base scheme (CiteBART-Base), the citation token in a local context is masked to learn to predict the citation.
• HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation Prediction
  10 Oct 2024 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  Second, logical relationships between papers are implicit, and directly prompting an LLM to predict citations may result in surface-level textual similarities rather than the deeper logical reasoning.
• Citation-Enhanced Generation for LLM-based Chatbots
  25 Feb 2024 1 repository listed
  Note that our method is a training-free plug-and-play plugin that is capable of various LLMs.
• Encoding Multi-Domain Scientific Papers by Ensembling Multiple CLS Tokens
  8 Sep 2023 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  Many useful tasks on scientific documents, such as topic classification and citation prediction, involve corpora that span multiple scientific domains.
• Galactica: A Large Language Model for Science
  16 Nov 2022 1 repository listed Syntology ran 0 of 2 samples · 2 unverified
  We believe these results demonstrate the potential for language models as a new interface for science.
• No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval
  6 Jun 2022 1 repository listed
  This has made distilled and dense models, due to latency constraints, the go-to choice for deployment in real-world retrieval applications.
• SGPT: GPT Sentence Embeddings for Semantic Search
  17 Feb 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  To this end, we propose SGPT to use decoders for sentence embeddings and semantic search via prompting or fine-tuning.
• Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings
  14 Feb 2022 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  Learning scientific document representations can be substantially improved through contrastive learning objectives, where the challenge lies in creating positive and negative training samples that encode the desired…
• Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks
  22 May 2019 1 repository listed
  For the problem of patent citations, we observe that forecasting a patent's chain of citations benefits from not only the patent's history itself but also from the historical citations of assignees and inventors…

Syntology lines on 8 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.