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20212026
most citedSarcasm Detection in a Disaster Context

3 citations · 15 across the 41 of their papers we have counts for

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cs.LG2026

CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction

Mohammad Anas Jawad, Cornelia Caragea

Existing calibration methods for Large Language Models (LLMs) often overlook a critical dimension of trustworthiness: a model's behavioral robustness to irrelevant or misleading in…

cs.LG2025

LLM-Guided Co-Training for Text Classification

Md Mezbaur Rahman, Cornelia Caragea

In this paper, we introduce a novel weighted co-training approach that is guided by Large Language Models (LLMs). Namely, in our co-training approach, we use LLM labels on unlabele…

cs.LG2024

On the Design Space Between Transformers and Recursive Neural Nets

Jishnu Ray Chowdhury, Cornelia Caragea

In this paper, we study two classes of models, Recursive Neural Networks (RvNNs) and Transformers, and show that a tight connection between them emerges from the recent development…

cs.LG2024

Investigating Recurrent Transformers with Dynamic Halt

Jishnu Ray Chowdhury, Cornelia Caragea

In this paper, we comprehensively study the inductive biases of two major approaches to augmenting Transformers with a recurrent mechanism: (1) the approach of incorporating a dept…

cs.LG2023

Recursion in Recursion: Two-Level Nested Recursion for Length Generalization with Scalability

Jishnu Ray Chowdhury, Cornelia Caragea

Binary Balanced Tree RvNNs (BBT-RvNNs) enforce sequence composition according to a preset balanced binary tree structure. Thus, their non-linear recursion depth is just

cs.LG2023

Efficient Beam Tree Recursion

Jishnu Ray Chowdhury, Cornelia Caragea

Beam Tree Recursive Neural Network (BT-RvNN) was recently proposed as a simple extension of Gumbel Tree RvNN and it was shown to achieve state-of-the-art length generalization perf…