3 papers
cs.LG2026
Can LLMs Compress (and Decompress)? Evaluating Code Understanding and Execution via Invertibility
Nickil Maveli, Antonio Vergari, Shay B. Cohen
LLMs demonstrate strong performance on code benchmarks, yet consistent reasoning across forward and backward execution remains elusive. We present RoundTripCodeEval (RTCE), a bench…
cs.SE2024
What can Large Language Models Capture about Code Functional Equivalence?
Nickil Maveli, Antonio Vergari, Shay B. Cohen
Code-LLMs, LLMs pre-trained on large code corpora, have shown great progress in learning rich representations of the structure and syntax of code, successfully using it to generate…
cs.CL2020
EdinburghNLP at WNUT-2020 Task 2: Leveraging Transformers with Generalized Augmentation for Identifying Informativeness in COVID-19 Tweets
Nickil Maveli
Twitter and, in general, social media has become an indispensable communication channel in times of emergency. The ubiquitousness of smartphone gadgets enables people to declare an…