2 citations · 5 across the 12 of their papers we have counts for
7 papers · 1 filter
Cognitive Agent Compilation for Explicit Problem Solver Modeling
Hyeongdon Moon, Carolyn Rosé, John Stamper
Large language models (LLMs) are widely used for tutoring, feedback generation, and content creation, but their broad pretraining makes them hard to constrain and poor substitutes…
ChartEditBench: Evaluating Grounded Multi-Turn Chart Editing in Multimodal Language Models
Manav Nitin Kapadnis, Lawanya Baghel, Atharva Naik +1
While Multimodal Large Language Models (MLLMs) perform strongly on single-turn chart generation, their ability to support real-world exploratory data analysis remains underexplored…
On Code-Induced Reasoning in LLMs
Abdul Waheed, Zhen Wu, Carolyn Rosé +1
Code data has been shown to enhance the reasoning capabilities of large language models (LLMs), but it remains unclear which aspects of code are most responsible. We investigate th…
Estimating Agreement by Chance for Sequence Annotation
Diya Li, Carolyn Rosé, Ao Yuan +1
In the field of natural language processing, correction of performance assessment for chance agreement plays a crucial role in evaluating the reliability of annotations. However, t…
Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research
Denis Newman-Griffis, Jill Fain Lehman, Carolyn Rosé +1
Natural language processing (NLP) research combines the study of universal principles, through basic science, with applied science targeting specific use cases and settings. Howeve…
RESPER: Computationally Modelling Resisting Strategies in Persuasive Conversations
Ritam Dutt, Sayan Sinha, Rishabh Joshi +5
Modelling persuasion strategies as predictors of task outcome has several real-world applications and has received considerable attention from the computational linguistics communi…
Towards Open Domain Event Trigger Identification using Adversarial Domain Adaptation
Aakanksha Naik, Carolyn Rosé
We tackle the task of building supervised event trigger identification models which can generalize better across domains. Our work leverages the adversarial domain adaptation (ADA)…