activity
20122026
most citedLearning and Evaluating Contextual Embedding of Source Code

155 citations · 309 across the 27 of their papers we have counts for

collaborators
Showing cs.AIShow all

7 papers · 1 filter

cs.AI2026

Narrative World Model: Narratology-Grounded Writer Memory for Long-Form Fiction

Mohammad Saifullah, Thomas Kornmaier, Taaha Kazi +3

Long-form fiction writers need memory that answers multi-hop questions about evolving story state: who knows a secret and when they learned it, whether an event preceded the narrat…

cs.AI2024

MASAI: Modular Architecture for Software-engineering AI Agents

Daman Arora, Atharv Sonwane, Nalin Wadhwa +5

A common method to solve complex problems in software engineering, is to divide the problem into multiple sub-problems. Inspired by this, we propose a Modular Architecture for Soft…

cs.AI2023★ 3 cited

Frustrated with Code Quality Issues? LLMs can Help!

Nalin Wadhwa, Jui Pradhan, Atharv Sonwane +5

As software projects progress, quality of code assumes paramount importance as it affects reliability, maintainability and security of software. For this reason, static analysis to…

cs.AI2022

BNSynth: Bounded Boolean Functional Synthesis

Ravi Raja, Stanly Samuel, Chiranjib Bhattacharyya +2

The automated synthesis of correct-by-construction Boolean functions from logical specifications is known as the Boolean Functional Synthesis (BFS) problem. BFS has many applicatio…

cs.AI2021★ 1 cited

Tele-EvalNet: A Low-cost, Teleconsultation System for Home based Rehabilitation of Stroke Survivors using Multiscale CNN-LSTM Architecture

Aditya Kanade, Mansi Sharma, M. Manivannan

Technology has an important role to play in the field of Rehabilitation, improving patient outcomes and reducing healthcare costs. However, existing approaches lack clinical valida…

cs.AI2018★ 12 cited

Greybox fuzzing as a contextual bandits problem

Ketan Patil, Aditya Kanade

Greybox fuzzing is one of the most useful and effective techniques for the bug detection in large scale application programs. It uses minimal amount of instrumentation. American Fu…

cs.AI2018★ 22 cited

Deep Reinforcement Learning for Programming Language Correction

Rahul Gupta, Aditya Kanade, Shirish Shevade

Novice programmers often struggle with the formal syntax of programming languages. To assist them, we design a novel programming language correction framework amenable to reinforce…