4 citations · 5 across the 4 of their papers we have counts for
4 papers
LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models
Shibo Hao, Yi Gu, Haotian Luo +9
Generating accurate step-by-step reasoning is essential for Large Language Models (LLMs) to address complex problems and enhance robustness and interpretability. Despite the flux o…
SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank
Dheeraj Mekala, Adithya Samavedhi, Chengyu Dong +1
Deep neural classifiers trained with cross-entropy loss (CE loss) often suffer from poor calibration, necessitating the task of out-of-distribution (OOD) detection. Traditional sup…
Transformer-based Models for Long-Form Document Matching: Challenges and Empirical Analysis
Akshita Jha, Adithya Samavedhi, Vineeth Rakesh +2
Recent advances in the area of long document matching have primarily focused on using transformer-based models for long document encoding and matching. There are two primary challe…
Supervised Contrastive Learning for Interpretable Long-Form Document Matching
Akshita Jha, Vineeth Rakesh, Jaideep Chandrashekar +2
Recent advancements in deep learning techniques have transformed the area of semantic text matching. However, most state-of-the-art models are designed to operate with short docume…