10 citations · 20 across the 9 of their papers we have counts for
11 papers
Is This Just Fantasy? Language Model Representations Reflect Human Judgments of Event Plausibility
Michael A. Lepori, Jennifer Hu, Ishita Dasgupta +3
Language models (LMs) are used for a diverse range of tasks, from question answering to writing fantastical stories. In order to reliably accomplish these tasks, LMs must be able t…
Utility-inspired Reward Transformations Improve Reinforcement Learning Training of Language Models
Roberto-Rafael Maura-Rivero, Chirag Nagpal, Roma Patel +1
Current methods that train large language models (LLMs) with reinforcement learning feedback, often resort to averaging outputs of multiple rewards functions during training. This…
Skill Generalization with Verbs
Rachel Ma, Lyndon Lam, Benjamin A. Spiegel +6
It is imperative that robots can understand natural language commands issued by humans. Such commands typically contain verbs that signify what action should be performed on a give…
Steering Language Models with Game-Theoretic Solvers
Ian Gemp, Roma Patel, Yoram Bachrach +6
Mathematical models of interactions among rational agents have long been studied in game theory. However these interactions are often over a small set of discrete game actions whic…
Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches
Daniel Fried, Nicholas Tomlin, Jennifer Hu +2
People rely heavily on context to enrich meaning beyond what is literally said, enabling concise but effective communication. To interact successfully and naturally with people, us…
RLang: A Declarative Language for Describing Partial World Knowledge to Reinforcement Learning Agents
Rafael Rodriguez-Sanchez, Benjamin A. Spiegel, Jennifer Wang +3
We introduce RLang, a domain-specific language (DSL) for communicating domain knowledge to an RL agent. Unlike existing RL DSLs that ground to \textit{single} elements of a decisio…
Planning with State Abstractions for Non-Markovian Task Specifications
Yoonseon Oh, Roma Patel, Thao Nguyen +3
Often times, we specify tasks for a robot using temporal language that can also span different levels of abstraction. The example command ``go to the kitchen before going to the se…
Probing What Different NLP Tasks Teach Machines about Function Word Comprehension
Najoung Kim, Roma Patel, Adam Poliak +9
We introduce a set of nine challenge tasks that test for the understanding of function words. These tasks are created by structurally mutating sentences from existing datasets to t…
Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling
Alex Wang, Jan Hula, Patrick Xia +13
Natural language understanding has recently seen a surge of progress with the use of sentence encoders like ELMo (Peters et al., 2018a) and BERT (Devlin et al., 2019) which are pre…
A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature
Benjamin Nye, Junyi Jessy Li, Roma Patel +4
We present a corpus of 5,000 richly annotated abstracts of medical articles describing clinical randomized controlled trials. Annotations include demarcations of text spans that de…
Syntactic Patterns Improve Information Extraction for Medical Search
Roma Patel, Yinfei Yang, Iain Marshall +2
Medical professionals search the published literature by specifying the type of patients, the medical intervention(s) and the outcome measure(s) of interest. In this paper we demon…