Publications (74)
Adversarial Learning for Neural Dialogue Generation
Jiwei Li, Will Monroe, Tianlin Shi +3
In this paper, drawing intuition from the Turing test, we propose using adversarial training for open-domain dialogue generation: the system is trained to produce sequences that ar…
UniIR: Training and Benchmarking Universal Multimodal Information Retrievers
Cong Wei, Yang Chen, Haonan Chen +5
Existing information retrieval (IR) models often assume a homogeneous format, limiting their applicability to diverse user needs, such as searching for images with text description…
Process-Level Representation of Scientific Protocols with Interactive Annotation
Ronen Tamari, Fan Bai, Alan Ritter +1
We develop Process Execution Graphs (PEG), a document-level representation of real-world wet lab biochemistry protocols, addressing challenges such as cross-sentence relations, lon…
What are Foundation Models Cooking in the Post-Soviet World?
Anton Lavrouk, Tarek Naous, Alan Ritter +1
The culture of the Post-Soviet states is complex, shaped by a turbulent history that continues to influence current events. In this study, we investigate the Post-Soviet cultural f…
Schema-Driven Information Extraction from Heterogeneous Tables
Fan Bai, Junmo Kang, Gabriel Stanovsky +3
In this paper, we explore the question of whether large language models can support cost-efficient information extraction from tables. We introduce schema-driven information extrac…
TweeTime: A Minimally Supervised Method for Recognizing and Normalizing Time Expressions in Twitter
Jeniya Tabassum, Alan Ritter, Wei Xu
We describe TweeTIME, a temporal tagger for recognizing and normalizing time expressions in Twitter. Most previous work in social media analysis has to rely on temporal resolvers t…