115 citations · 219 across the 12 of their papers we have counts for
6 papers · 1 filter
Few-Shot Adaptation for Parsing Contextual Utterances with LLMs
Kevin Lin, Patrick Xia, Hao Fang
We evaluate the ability of semantic parsers based on large language models (LLMs) to handle contextual utterances. In real-world settings, there typically exists only a limited num…
Natural Language Decomposition and Interpretation of Complex Utterances
Harsh Jhamtani, Hao Fang, Patrick Xia +3
Designing natural language interfaces has historically required collecting supervised data to translate user requests into carefully designed intent representations. This requires…
Task-Aware Specialization for Efficient and Robust Dense Retrieval for Open-Domain Question Answering
Hao Cheng, Hao Fang, Xiaodong Liu +1
Given its effectiveness on knowledge-intensive natural language processing tasks, dense retrieval models have become increasingly popular. Specifically, the de-facto architecture f…
When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems
Elias Stengel-Eskin, Emmanouil Antonios Platanios, Adam Pauls +5
In natural language understanding (NLU) production systems, users' evolving needs necessitate the addition of new features over time, indexed by new symbols added to the meaning re…
Talking to the crowd: What do people react to in online discussions?
Aaron Jaech, Victoria Zayats, Hao Fang +2
This paper addresses the question of how language use affects community reaction to comments in online discussion forums, and the relative importance of the message vs. the messeng…
Language Models for Image Captioning: The Quirks and What Works
Jacob Devlin, Hao Cheng, Hao Fang +5
Two recent approaches have achieved state-of-the-art results in image captioning. The first uses a pipelined process where a set of candidate words is generated by a convolutional…