565 citations · 688 across the 19 of their papers we have counts for
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What Do NLP Researchers Believe? Results of the NLP Community Metasurvey
Julian Michael, Ari Holtzman, Alicia Parrish +8
We present the results of the NLP Community Metasurvey. Run from May to June 2022, the survey elicited opinions on controversial issues, including industry influence in the field,…
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448
Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…
SQuALITY: Building a Long-Document Summarization Dataset the Hard Way
Alex Wang, Richard Yuanzhe Pang, Angelica Chen +2
Summarization datasets are often assembled either by scraping naturally occurring public-domain summaries -- which are nearly always in difficult-to-work-with technical domains --…
Teaching BERT to Wait: Balancing Accuracy and Latency for Streaming Disfluency Detection
Angelica Chen, Vicky Zayats, Daniel D. Walker +1
In modern interactive speech-based systems, speech is consumed and transcribed incrementally prior to having disfluencies removed. This post-processing step is crucial for producin…
Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions
Alicia Parrish, Harsh Trivedi, Ethan Perez +4
Current QA systems can generate reasonable-sounding yet false answers without explanation or evidence for the generated answer, which is especially problematic when humans cannot r…
Training Language Models with Language Feedback
Jérémy Scheurer, Jon Ander Campos, Jun Shern Chan +3
Pretrained language models often do not perform tasks in ways that are in line with our preferences, e.g., generating offensive text or factually incorrect summaries. Recent work a…