79 citations · 94 across the 10 of their papers we have counts for
11 papers
Language Model Inversion
John X. Morris, Wenting Zhao, Justin T. Chiu +2
Language models produce a distribution over the next token; can we use this information to recover the prompt tokens? We consider the problem of language model inversion and show t…
Symbolic Planning and Code Generation for Grounded Dialogue
Justin T. Chiu, Wenting Zhao, Derek Chen +3
Large language models (LLMs) excel at processing and generating both text and code. However, LLMs have had limited applicability in grounded task-oriented dialogue as they are diff…
Abductive Commonsense Reasoning Exploiting Mutually Exclusive Explanations
Wenting Zhao, Justin T. Chiu, Claire Cardie +1
Abductive reasoning aims to find plausible explanations for an event. This style of reasoning is critical for commonsense tasks where there are often multiple plausible explanation…
HOP, UNION, GENERATE: Explainable Multi-hop Reasoning without Rationale Supervision
Wenting Zhao, Justin T. Chiu, Claire Cardie +1
Explainable multi-hop question answering (QA) not only predicts answers but also identifies rationales, i. e. subsets of input sentences used to derive the answers. This problem ha…
Unsupervised Text Deidentification
John X. Morris, Justin T. Chiu, Ramin Zabih +1
Deidentification seeks to anonymize textual data prior to distribution. Automatic deidentification primarily uses supervised named entity recognition from human-labeled data points…
Teal: Learning-Accelerated Optimization of WAN Traffic Engineering
Zhiying Xu, Francis Y. Yan, Rachee Singh +3
The rapid expansion of global cloud wide-area networks (WANs) has posed a challenge for commercial optimization engines to efficiently solve network traffic engineering (TE) proble…
Low-Rank Constraints for Fast Inference in Structured Models
Justin T. Chiu, Yuntian Deng, Alexander M. Rush
Structured distributions, i.e. distributions over combinatorial spaces, are commonly used to learn latent probabilistic representations from observed data. However, scaling these m…
Reference-Centric Models for Grounded Collaborative Dialogue
Daniel Fried, Justin T. Chiu, Dan Klein
We present a grounded neural dialogue model that successfully collaborates with people in a partially-observable reference game. We focus on a setting where two agents each observe…
Scaling Hidden Markov Language Models
Justin T. Chiu, Alexander M. Rush
The hidden Markov model (HMM) is a fundamental tool for sequence modeling that cleanly separates the hidden state from the emission structure. However, this separation makes it dif…
Tensor Variable Elimination for Plated Factor Graphs
Fritz Obermeyer, Eli Bingham, Martin Jankowiak +4
A wide class of machine learning algorithms can be reduced to variable elimination on factor graphs. While factor graphs provide a unifying notation for these algorithms, they do n…
Latent Alignment and Variational Attention
Yuntian Deng, Yoon Kim, Justin Chiu +2
Neural attention has become central to many state-of-the-art models in natural language processing and related domains. Attention networks are an easy-to-train and effective method…