Search Results for author:
Found 27 papers, 8 papers with code
GSO: Challenging Software Optimization Tasks for Evaluating SWE-Agents
Developing high-performance software is a complex task that requires specialized expertise.
R2E-Gym: Procedural Environments and Hybrid Verifiers for Scaling Open-Weights SWE Agents
Improving open-source models on real-world SWE tasks (solving GITHUB issues) faces two key challenges: 1) scalable curation of execution environments to train these models, and, 2) optimal scaling of test-time compute.
Challenges and Paths Towards AI for Software Engineering
First, we provide a structured taxonomy of concrete tasks in AI for software engineering, emphasizing the many other tasks in software engineering beyond code generation and completion.
QuFeX: Quantum feature extraction module for hybrid quantum-classical deep neural networks
We introduce Quantum Feature Extraction (QuFeX), a novel quantum machine learning module.
Syzygy: Dual Code-Test C to (safe) Rust Translation using LLMs and Dynamic Analysis
We validate the translation by testing equivalence with the source C program on a set of inputs.
SelfCodeAlign: Self-Alignment for Code Generation
In our primary experiments, we use SelfCodeAlign with CodeQwen1. 5-7B to generate a dataset of 74k instruction-response pairs.
BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions
In addition, using multiple tools to solve a task needs compositional reasoning by accurately understanding complex instructions.
Ranked #1 on
Code Generation
on BigCodeBench-Instruct
RAFT: Adapting Language Model to Domain Specific RAG
In this paper, we present Retrieval Augmented FineTuning (RAFT), a training recipe that improves the model's ability to answer questions in a "open-book" in-domain settings.
LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
Large Language Models (LLMs) applied to code-related applications have emerged as a prominent field, attracting significant interest from both academia and industry.
The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?
In this work, we focus on these counterfeit samples: programs sampled from a language model that 1) have a high enough log-probability to be generated at a moderate temperature and 2) pass weak correctness checks.
StarCoder 2 and The Stack v2: The Next Generation
Our large model, StarCoder2- 15B, significantly outperforms other models of comparable size.
Ranked #36 on
Code Generation
on MBPP
LLM-Assisted Code Cleaning For Training Accurate Code Generators
In this work, we investigate data quality for code and find that making the code more structured and readable leads to improved code generation performance of the system.
Revisiting Prompt Engineering via Declarative Crowdsourcing
Large language models (LLMs) are incredibly powerful at comprehending and generating data in the form of text, but are brittle and error-prone.
SentEmojiBot: Empathising Conversations Generation with Emojis
The increasing use of dialogue agents makes it extremely desirable for them to understand and acknowledge the implied emotions to respond like humans with empathy.
Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent
Decision trees provide a rich family of highly non-linear but efficient models, due to which they continue to be the go-to family of predictive models by practitioners across domains.
Bollyrics: Automatic Lyrics Generator for Romanised Hindi
Song lyrics convey a meaningful story in a creative manner with complex rhythmic patterns.
What's in a Name? Are BERT Named Entity Representations just as Good for any other Name?
We evaluate named entity representations of BERT-based NLP models by investigating their robustness to replacements from the same typed class in the input.
A Multi-Dimensional View of Aggression when voicing Opinion
The advent of social media has immensely proliferated the amount of opinions and arguments voiced on the internet.
PlantDoc: A Dataset for Visual Plant Disease Detection
Early detection of plant diseases remains difficult due to the lack of lab infrastructure and expertise.
NLPExplorer: Exploring the Universe of NLP Papers
Also, it provides temporal statistics such as yearwise popularity of topics, datasets, and seminal papers.
On the Robustness of Human Pose Estimation
This paper provides a comprehensive and exhaustive study of adversarial attacks on human pose estimation models and the evaluation of their robustness.
A House United: Bridging the Script and Lexical Barrier between Hindi and Urdu
With respect to text processing, addressing the differences between the Hindi and Urdu texts would be beneficial in the following ways: (a) instead of training separate models, their individual resources can be augmented to train single, unified models for better generalization, and (b) their individual text processing applications can be used interchangeably under varied resource conditions.
