25 citations · 80 across the 23 of their papers we have counts for
7 papers · 1 filter
Bifurcated Attention: Accelerating Massively Parallel Decoding with Shared Prefixes in LLMs
Ben Athiwaratkun, Sujan Kumar Gonugondla, Sanjay Krishna Gouda +10
This study introduces bifurcated attention, a method designed to enhance language model inference in shared-context batch decoding scenarios. Our approach addresses the challenge o…
CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion
Yangruibo Ding, Zijian Wang, Wasi Uddin Ahmad +8
Code completion models have made significant progress in recent years, yet current popular evaluation datasets, such as HumanEval and MBPP, predominantly focus on code completion t…
Exploring Continual Learning for Code Generation Models
Prateek Yadav, Qing Sun, Hantian Ding +9
Large-scale code generation models such as Codex and CodeT5 have achieved impressive performance. However, libraries are upgraded or deprecated very frequently and re-training larg…
Greener yet Powerful: Taming Large Code Generation Models with Quantization
Xiaokai Wei, Sujan Gonugondla, Wasi Ahmad +13
ML-powered code generation aims to assist developers to write code in a more productive manner, by intelligently generating code blocks based on natural language prompts. Recently,…
Linear Spaces of Meanings: Compositional Structures in Vision-Language Models
Matthew Trager, Pramuditha Perera, Luca Zancato +3
We investigate compositional structures in data embeddings from pre-trained vision-language models (VLMs). Traditionally, compositionality has been associated with algebraic operat…
ReCode: Robustness Evaluation of Code Generation Models
Shiqi Wang, Zheng Li, Haifeng Qian +11
Code generation models have achieved impressive performance. However, they tend to be brittle as slight edits to a prompt could lead to very different generations; these robustness…