24 citations · 26 across the 7 of their papers we have counts for
8 papers
CORVUS: Context Optimization and Reduction Via Underlying Synchronization for LLM Coding Agents
Mingwei Zheng, David OBrien, Siwei Cui +4
LLM coding agents operate by constructing trajectories that accumulate reasoning, tool calls, and results to enable multi-step decision-making. However, the conventional append-onl…
SpecAgent: A Speculative Retrieval and Forecasting Agent for Code Completion
George Ma, Anurag Koul, Qi Chen +6
Large Language Models (LLMs) excel at code-related tasks but often struggle in realistic software repositories, where project-specific APIs and cross-file dependencies are crucial.…
UTFix: Change Aware Unit Test Repairing using LLM
Shanto Rahman, Sachit Kuhar, Berk Cirisci +5
Software updates, including bug repair and feature additions, are frequent in modern applications but they often leave test suites outdated, resulting in undetected bugs and increa…
LibEvolutionEval: A Benchmark and Study for Version-Specific Code Generation
Sachit Kuhar, Wasi Uddin Ahmad, Zijian Wang +6
Recent advancements in code completion models have primarily focused on local file contexts. However, these studies do not fully capture the complexity of real-world software devel…
PLUM: Improving Inference Efficiency By Leveraging Repetition-Sparsity Trade-Off
Sachit Kuhar, Yash Jain, Alexey Tumanov
Efficient inference of Deep Neural Networks (DNNs) on resource-constrained edge devices is essential. Quantization and sparsity are key techniques that translate to repetition and…
Learning to Discern: Imitating Heterogeneous Human Demonstrations with Preference and Representation Learning
Sachit Kuhar, Shuo Cheng, Shivang Chopra +2
Practical Imitation Learning (IL) systems rely on large human demonstration datasets for successful policy learning. However, challenges lie in maintaining the quality of collected…
Signed Binary Weight Networks
Sachit Kuhar, Alexey Tumanov, Judy Hoffman
Efficient inference of Deep Neural Networks (DNNs) is essential to making AI ubiquitous. Two important algorithmic techniques have shown promise for enabling efficient inference -…
Offline Visual Representation Learning for Embodied Navigation
Karmesh Yadav, Ram Ramrakhya, Arjun Majumdar +5
How should we learn visual representations for embodied agents that must see and move? The status quo is tabula rasa in vivo, i.e. learning visual representations from scratch whil…