28 citations · 106 across the 7 of their papers we have counts for
9 papers
InvestigationWorlds: An Agentic Environment for Legal Investigation
Albert Yu Sun, Andrew Benard, Sil Hamilton +8
We introduce InvestigationWorlds, an agentic environment for legal investigation. We build on an underused artifact of U.S. civil litigation: the summary judgment motion. This moti…
Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds
Igor Labutov, Bishan Yang, Anusha Prakash +1
Question Answering (QA), as a research field, has primarily focused on either knowledge bases (KBs) or free text as a source of knowledge. These two sources have historically shape…
Leveraging Knowledge Bases in LSTMs for Improving Machine Reading
Bishan Yang, Tom Mitchell
This paper focuses on how to take advantage of external knowledge bases (KBs) to improve recurrent neural networks for machine reading. Traditional methods that exploit knowledge f…
Learning to Learn Semantic Parsers from Natural Language Supervision
Igor Labutov, Bishan Yang, Tom Mitchell
As humans, we often rely on language to learn language. For example, when corrected in a conversation, we may learn from that correction, over time improving our language fluency.…
End-to-End Learning for Structured Prediction Energy Networks
David Belanger, Bishan Yang, Andrew McCallum
Structured Prediction Energy Networks (SPENs) are a simple, yet expressive family of structured prediction models (Belanger and McCallum, 2016). An energy function over candidate s…
Joint Extraction of Events and Entities within a Document Context
Bishan Yang, Tom Mitchell
Events and entities are closely related; entities are often actors or participants in events and events without entities are uncommon. The interpretation of events and entities is…
A Hierarchical Distance-dependent Bayesian Model for Event Coreference Resolution
Bishan Yang, Claire Cardie, Peter Frazier
We present a novel hierarchical distance-dependent Bayesian model for event coreference resolution. While existing generative models for event coreference resolution are completely…
Embedding Entities and Relations for Learning and Inference in Knowledge Bases
Bishan Yang, Wen-tau Yih, Xiaodong He +2
We consider learning representations of entities and relations in KBs using the neural-embedding approach. We show that most existing models, including NTN (Socher et al., 2013) an…
Learning Multi-Relational Semantics Using Neural-Embedding Models
Bishan Yang, Wen-tau Yih, Xiaodong He +2
In this paper we present a unified framework for modeling multi-relational representations, scoring, and learning, and conduct an empirical study of several recent multi-relational…