Established and new NLP authors are migrating from *ACL venues to general ML venues, with ML venues conferring a large content-matched citation premium.
SciRepEval: A multi-format benchmark for scientific document representations
4 Pith papers cite this work, alongside 50 external citations. Polarity classification is still indexing.
4
Pith papers citing it
50
external citations · OpenAlex
years
2026 4representative citing papers
Phantom collaborators—topically similar authors distant in the coauthor graph—become actual coauthors 16-33 times more often than baselines, with a 68-fold similarity gradient.
A new benchmark (IG-Bench) reveals that LLM-based scientists fail at compositional lineage reasoning, with the best system reaching only 27.3% exact accuracy.
Many-shot ICL with LLMs matches or exceeds supervised BERT on NER and generates high-quality labels for low-resource settings, producing ~10% absolute F1 gains when used to fine-tune BERT.
citing papers explorer
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The Future of NLP may not be at NLP Conferences: Scholarly Migration Patterns in Natural Language Processing
Established and new NLP authors are migrating from *ACL venues to general ML venues, with ML venues conferring a large content-matched citation premium.
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Beyond coauthorship: semantic structure and phantom collaborators in transportation research, 1967--2025
Phantom collaborators—topically similar authors distant in the coauthor graph—become actual coauthors 16-33 times more often than baselines, with a 68-fold similarity gradient.
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Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation
A new benchmark (IG-Bench) reveals that LLM-based scientists fail at compositional lineage reasoning, with the best system reaching only 27.3% exact accuracy.
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Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity Recognition
Many-shot ICL with LLMs matches or exceeds supervised BERT on NER and generates high-quality labels for low-resource settings, producing ~10% absolute F1 gains when used to fine-tune BERT.