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20172022
most citedLaMDA: Language Models for Dialog Applications

708 citations · 727 across the 2 of their papers we have counts for

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cs.CL2022708 cited

LaMDA: Language Models for Dialog Applications

Romal Thoppilan, Daniel De Freitas, Jamie Hall +57

We present LaMDA: Language Models for Dialog Applications. LaMDA is a family of Transformer-based neural language models specialized for dialog, which have up to 137B parameters an…

cs.CL2021

Decontextualization: Making Sentences Stand-Alone

Eunsol Choi, Jennimaria Palomaki, Matthew Lamm +3

Models for question answering, dialogue agents, and summarization often interpret the meaning of a sentence in a rich context and use that meaning in a new context. Taking excerpts…

cs.CL2020

QED: A Framework and Dataset for Explanations in Question Answering

Matthew Lamm, Jennimaria Palomaki, Chris Alberti +4

A question answering system that in addition to providing an answer provides an explanation of the reasoning that leads to that answer has potential advantages in terms of debuggab…

cs.CL2019

Ellipsis Resolution as Question Answering: An Evaluation

Rahul Aralikatte, Matthew Lamm, Daniel Hardt +1

Most, if not all forms of ellipsis (e.g., so does Mary) are similar to reading comprehension questions (what does Mary do), in that in order to resolve them, we need to identify an…

cs.CL2018

Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts

Matthew Lamm, Arun Tejasvi Chaganty, Christopher D. Manning +2

To understand a sentence like "whereas only 10% of White Americans live at or below the poverty line, 28% of African Americans do" it is important not only to identify individual f…