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Research - Papers

Explore a selection of our published work on a variety of key research challenges in AI.

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JAMDEC: Unsupervised Authorship Obfuscation using Constrained Decoding over Small Language Models

Jillian R. FisherXiming LuJaehun JungYejin Choi
2024
NAACL

The permanence of online content combined with the enhanced authorship identification techniques calls for stronger computational methods to protect the identity and privacy of online authorship… 

MacGyver: Are Large Language Models Creative Problem Solvers?

Yufei TianAbhilasha RavichanderLianhui QinFaeze Brahman
2024
NAACL

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

Jaehun JungPeter WestLiwei JiangYejin Choi
2024
NAACL

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

Maitrey MehtaValentina PyatkinVivek Srikumar
2024
NAACL

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

Monica MunnangiSergey FeldmanByron C WallaceAakanksha Naik
2024
NAACL 2024

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

Sanchaita HazraBodhisattwa Prasad Majumder
2024
North American Chapter of the Association for Computational Linguistics

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… 

SelfGoal: Your Language Agents Already Know How to Achieve High-level Goals

Ruihan YangJiangjie ChenYikai ZhangDeqing Yang
2024
technical report

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

Yuling GuOyvind TafjordPeter Clark
2024
ACL

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

Nouran SolimanHyeonsu B. KangMatthew LatzkeDavid R. Karger
2024
CHI

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

Yoonjoo LeeHyeonsu B KangMatt LatzkePao Siangliulue
2024
CHI

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…