3 citations · 9 across the 8 of their papers we have counts for
6 papers · 1 filter
Gradient-Controlled Decoding: A Safety Guardrail for LLMs with Dual-Anchor Steering
Purva Chiniya, Kevin Scaria, Sagar Chaturvedi
Large language models (LLMs) remain susceptible to jailbreak and direct prompt-injection attacks, yet the strongest defensive filters frequently over-refuse benign queries and degr…
Cutting Through the Noise: Boosting LLM Performance on Math Word Problems
Ujjwala Anantheswaran, Himanshu Gupta, Kevin Scaria +3
Large Language Models (LLMs) excel at various tasks, including solving math word problems (MWPs), but struggle with real-world problems containing irrelevant information. To addres…
Embarrassingly Simple Unsupervised Aspect Based Sentiment Tuple Extraction
Kevin Scaria, Abyn Scaria, Ben Scaria
Aspect Based Sentiment Analysis (ABSA) tasks involve the extraction of fine-grained sentiment tuples from sentences, aiming to discern the author's opinions. Conventional methodolo…
TarGEN: Targeted Data Generation with Large Language Models
Himanshu Gupta, Kevin Scaria, Ujjwala Anantheswaran +5
The rapid advancement of large language models (LLMs) has sparked interest in data synthesis techniques, aiming to generate diverse and high-quality synthetic datasets. However, th…
InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis
Kevin Scaria, Himanshu Gupta, Siddharth Goyal +3
We introduce InstructABSA, an instruction learning paradigm for Aspect-Based Sentiment Analysis (ABSA) subtasks. Our method introduces positive, negative, and neutral examples to e…
"John is 50 years old, can his son be 65?" Evaluating NLP Models' Understanding of Feasibility
Himanshu Gupta, Neeraj Varshney, Swaroop Mishra +5
In current NLP research, large-scale language models and their abilities are widely being discussed. Some recent works have also found notable failures of these models. Often these…