Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
MacGyver: Are Large Language Models Creative Problem Solvers?
We explore the creative problem-solving capabilities of modern LLMs in a novel constrained setting. To this end, we create MACGYVER, an automatically generated dataset consisting of over 1,600…
Impossible Distillation: from Low-Quality Model to High-Quality Dataset&Model for Summarization and Paraphrasing
We present Impossible Distillation, a novel framework for paraphrasing and sentence summarization, that distills a high-quality dataset and model from a low-quality teacher that itself cannot…
Promptly Predicting Structures: The Return of Inference
Prompt-based methods have been used extensively across NLP to build zero- and few-shot label predictors. Many NLP tasks are naturally structured: that is, their outputs consist of multiple labels…
On-the-fly Definition Augmentation of LLMs for Biomedical NER
Despite their general capabilities, LLMs still struggle on biomedical NER tasks, which are difficult due to the presence of specialized terminology and lack of training data. In this work we set out…
To Tell The Truth: Language of Deception and Language Models
Text-based false information permeates online discourses, yet evidence of people’s ability to discern truth from such deceptive textual content is scarce. We analyze a novel TV game show data where…
DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents
Automated scientific discovery promises to accelerate progress across scientific domains. However, developing and evaluating an AI agent's capacity for end-to-end scientific reasoning is challenging…
SelfGoal: Your Language Agents Already Know How to Achieve High-level Goals
Language agents powered by large language models (LLMs) are increasingly valuable as decision-making tools in domains such as gaming and programming. However, these agents often face challenges in…
Digital Socrates: Evaluating LLMs through explanation critiques
While LLMs can provide reasoned explanations along with their answers, the nature and quality of those explanations are still poorly understood. In response, our goal is to define a detailed way of…
Mitigating Barriers to Public Social Interaction with Meronymous Communication
In communities with social hierarchies, fear of judgment can discourage communication. While anonymity may alleviate some social pressure, fully anonymous spaces enable toxic behavior and hide the…
PaperWeaver: Enriching Topical Paper Alerts by Contextualizing Recommended Papers with User-collected Papers
With the rapid growth of scholarly archives, researchers subscribe to"paper alert"systems that periodically provide them with recommendations of recently published papers that are similar to…