Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
CHIME: LLM-Assisted Hierarchical Organization of Scientific Studies for Literature Review Support
Literature review requires researchers to synthesize a large amount of information and is increasingly challenging as the scientific literature expands. In this work, we investigate the potential of…
Few-shot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning
We consider the task of building a dialogue system that can motivate users to adopt positive lifestyle changes: Motivational Interviewing. Addressing such a task requires a system that can infer…
Overview of the Context24 Shared Task on Contextualizing Scientific Claims
To appropriately interpret and use scientific claims for sensemaking and decision-making, it is critical to contextualize them, not just with textual evidence that the claim was in fact asserted,…
The Unreasonable Effectiveness of Easy Training Data for Hard Tasks
How can we train models to perform well on hard test data when hard training data is by definition difficult to label correctly? This question has been termed the scalable oversight problem and has…
Data Contamination Report from the 2024 CONDA Shared Task
The 1st Workshop on Data Contamination (CONDA 2024) focuses on all relevant aspects of data contamination in natural language processing, where data contamination is understood as situations where…
The Illusion of State in State-Space Models
State-space models (SSMs) have emerged as a potential alternative architecture for building large language models (LLMs) compared to the previously ubiquitous transformer architecture. One…
Data-driven Discovery with Large Generative Models
With the accumulation of data at an unprecedented rate, its potential to fuel scientific discovery is growing exponentially. This position paper urges the Machine Learning (ML) community to exploit…
Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills
Large language models (LLMs) have recently been used for sequential decision making in interactive environments. However, leveraging environment reward signals for continual LLM actor improvement is…
Tell, Don't Show!: Language Guidance Eases Transfer Across Domains in Images and Videos
We introduce LaGTran, a novel framework that utilizes text supervision to guide robust transfer of discriminative knowledge from labeled source to unlabeled target data with domain gaps. While…
Climate sensitivity and relative humidity changes in global storm-resolving model simulations of climate change
The climate simulation frontier of a global storm-resolving model (GSRM; or k-scale model because of its kilometer-scale horizontal resolution) is deployed for climate change simulations. The…