activity
20182026
most citedAre Pre-trained Language Models Aware of Phrases? Simple but Strong Baselines for Grammar Induction

35 citations · 66 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Local Edits, Global Ripples: Replay-Informed Policy Adaptation for Workflow Synthesis

Manqing Mao, Hong Wang, Samson Koelle +8

Prompt-policy editing offers a practical way to improve agents that synthesize executable workflows without updating the underlying model. However, persistent prompt editing has tw…

cs.CL2022

Domain Mismatch Doesn't Always Prevent Cross-Lingual Transfer Learning

Daniel Edmiston, Phillip Keung, Noah A. Smith

Cross-lingual transfer learning without labeled target language data or parallel text has been surprisingly effective in zero-shot cross-lingual classification, question answering,…

cs.CL2020★ 30 cited

A Systematic Analysis of Morphological Content in BERT Models for Multiple Languages

Daniel Edmiston

This work describes experiments which probe the hidden representations of several BERT-style models for morphological content. The goal is to examine the extent to which discrete l…

cs.CL2020★ 35 cited

Are Pre-trained Language Models Aware of Phrases? Simple but Strong Baselines for Grammar Induction

Taeuk Kim, Jihun Choi, Daniel Edmiston +1

With the recent success and popularity of pre-trained language models (LMs) in natural language processing, there has been a rise in efforts to understand their inner workings. In…

cs.CL2018★ 1 cited

Dynamic Compositionality in Recursive Neural Networks with Structure-aware Tag Representations

Taeuk Kim, Jihun Choi, Daniel Edmiston +2

Most existing recursive neural network (RvNN) architectures utilize only the structure of parse trees, ignoring syntactic tags which are provided as by-products of parsing. We pres…