Search Results for author:
Found 7 papers, 1 papers with code
BaxBench: Can LLMs Generate Correct and Secure Backends?
The automatic generation of programs has long been a fundamental challenge in computer science.
BgGPT 1.0: Extending English-centric LLMs to other languages
We present BgGPT-Gemma-2-27B-Instruct and BgGPT-Gemma-2-9B-Instruct: continually pretrained and fine-tuned versions of Google's Gemma-2 models, specifically optimized for Bulgarian language understanding and generation.
Mitigating Catastrophic Forgetting in Language Transfer via Model Merging
As open-weight large language models (LLMs) achieve ever more impressive performances across a wide range of tasks in English, practitioners aim to adapt these models to different languages.
DeepCode AI Fix: Fixing Security Vulnerabilities with Large Language Models
We show that the task is difficult as it requires the model to learn long-range code relationships, a task that inherently relies on extensive amounts of training data.
TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer
The problem of fixing errors in programs has attracted substantial interest over the years.
Ranked #1 on
Program Repair
on TFix's Code Patches Data
Language-Independent Sentiment Analysis Using Subjectivity and Positional Information
We describe a novel language-independent approach to the task of determining the polarity, positive or negative, of the author's opinion on a specific topic in natural language text.
Learning a Static Analyzer from Data
In this paper we present a new, automated approach for creating static analyzers: instead of manually providing the various inference rules of the analyzer, the key idea is to learn these rules from a dataset of programs.
