2.2k citations · 3.1k across the 54 of their papers we have counts for
7 papers · 2 filters
Long Context Question Answering via Supervised Contrastive Learning
Avi Caciularu, Ido Dagan, Jacob Goldberger +1
Long-context question answering (QA) tasks require reasoning over a long document or multiple documents. Addressing these tasks often benefits from identifying a set of evidence sp…
Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity
Sheshera Mysore, Arman Cohan, Tom Hope
We present a new scientific document similarity model based on matching fine-grained aspects of texts. To train our model, we exploit a naturally-occurring source of supervision: s…
PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization
Wen Xiao, Iz Beltagy, Giuseppe Carenini +1
We introduce PRIMERA, a pre-trained model for multi-document representation with a focus on summarization that reduces the need for dataset-specific architectures and large amounts…
MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting
Anne Lauscher, Brandon Ko, Bailey Kuehl +4
Citation context analysis (CCA) is an important task in natural language processing that studies how and why scholars discuss each others' work. Despite decades of study, tradition…
FLEX: Unifying Evaluation for Few-Shot NLP
Jonathan Bragg, Arman Cohan, Kyle Lo +1
Few-shot NLP research is highly active, yet conducted in disjoint research threads with evaluation suites that lack challenging-yet-realistic testing setups and fail to employ care…
A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers
Pradeep Dasigi, Kyle Lo, Iz Beltagy +3
Readers of academic research papers often read with the goal of answering specific questions. Question Answering systems that can answer those questions can make consumption of the…
CDLM: Cross-Document Language Modeling
Avi Caciularu, Arman Cohan, Iz Beltagy +3
We introduce a new pretraining approach geared for multi-document language modeling, incorporating two key ideas into the masked language modeling self-supervised objective. First,…