64 citations · 135 across the 14 of their papers we have counts for
7 papers · 1 filter
Balancing Continuous Pre-Training and Instruction Fine-Tuning: Optimizing Instruction-Following in LLMs
Ishan Jindal, Chandana Badrinath, Pranjal Bharti +2
Large Language Models (LLMs) for public use require continuous pre-training to remain up-to-date with the latest data. The models also need to be fine-tuned with specific instructi…
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture
Bingsheng Yao, Ishan Jindal, Lucian Popa +8
Real-world domain experts (e.g., doctors) rarely annotate only a decision label in their day-to-day workflow without providing explanations. Yet, existing low-resource learning tec…
When to Use What: An In-Depth Comparative Empirical Analysis of OpenIE Systems for Downstream Applications
Kevin Pei, Ishan Jindal, Kevin Chen-Chuan Chang +2
Open Information Extraction (OpenIE) has been used in the pipelines of various NLP tasks. Unfortunately, there is no clear consensus on which models to use in which tasks. Muddying…
PriMeSRL-Eval: A Practical Quality Metric for Semantic Role Labeling Systems Evaluation
Ishan Jindal, Alexandre Rademaker, Khoi-Nguyen Tran +4
Semantic role labeling (SRL) identifies the predicate-argument structure in a sentence. This task is usually accomplished in four steps: predicate identification, predicate sense d…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Improved Semantic Role Labeling using Parameterized Neighborhood Memory Adaptation
Ishan Jindal, Ranit Aharonov, Siddhartha Brahma +2
Deep neural models achieve some of the best results for semantic role labeling. Inspired by instance-based learning that utilizes nearest neighbors to handle low-frequency context-…
CLAR: A Cross-Lingual Argument Regularizer for Semantic Role Labeling
Ishan Jindal, Yunyao Li, Siddhartha Brahma +1
Semantic role labeling (SRL) identifies predicate-argument structure(s) in a given sentence. Although different languages have different argument annotations, polyglot training, th…