2 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
GiVA: Gradient-Informed Bases for Vector-Based Adaptation
Neeraj Gangwar, Rishabh Deshmukh, Michael Shavlovsky +4
As model sizes continue to grow, parameter-efficient fine-tuning has emerged as a powerful alternative to full fine-tuning. While LoRA is widely adopted among these methods, recent…
Integrating Arithmetic Learning Improves Mathematical Reasoning in Smaller Models
Neeraj Gangwar, Suma P Bhat, Nickvash Kani
While large models pre-trained on high-quality data exhibit excellent performance on mathematical reasoning (e.g., GSM8k, MultiArith), it remains challenging to specialize smaller…
Highlighting Named Entities in Input for Auto-Formulation of Optimization Problems
Neeraj Gangwar, Nickvash Kani
Operations research deals with modeling and solving real-world problems as mathematical optimization problems. While solving mathematical systems is accomplished by analytical soft…
Semantic Representations of Mathematical Expressions in a Continuous Vector Space
Neeraj Gangwar, Nickvash Kani
Mathematical notation makes up a large portion of STEM literature, yet finding semantic representations for formulae remains a challenging problem. Because mathematical notation is…