:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ghaisas, Smita, Singhal, Anmol
Format:	Preprint
Published:	2024
Subjects:	Software Engineering Computation and Language
Online Access:	https://arxiv.org/abs/2402.16977
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Requirements Elicitation Follow-Up Question Generation
by: Shen, Yuchen, et al.
Published: (2025)

Legal Requirements Translation from Law
by: Singhal, Anmol, et al.
Published: (2025)

Generating Clarification Questions for Disambiguating Contracts
by: Singhal, Anmol, et al.
Published: (2024)

From Legal Text to Tech Specs: Generative AI's Interpretation of Consent in Privacy Law
by: Kesari, Aniket, et al.
Published: (2025)

GR-NLP-TOOLKIT: An Open-Source NLP Toolkit for Modern Greek
by: Loukas, Lefteris, et al.
Published: (2024)

A Low-Resource Speech-Driven NLP Pipeline for Sinhala Dyslexia Assistance
by: Perera, Peshala, et al.
Published: (2025)

Bias Testing and Mitigation in Black Box LLMs using Metamorphic Relations
by: Salimian, Sina, et al.
Published: (2025)

Replication in Requirements Engineering: the NLP for RE Case
by: Abualhaija, Sallam, et al.
Published: (2023)

Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code
by: Zhang, Ziyin, et al.
Published: (2023)

NLP4RE Tools: Classification, Overview, and Management
by: Frattini, Julian, et al.
Published: (2024)

LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigation
by: Zhang, Ziyao, et al.
Published: (2024)

Is Your AI-Generated Code Really Safe? Evaluating Large Language Models on Secure Code Generation with CodeSecEval
by: Wang, Jiexin, et al.
Published: (2024)

An Empirical Analysis of Static Analysis Methods for Detection and Mitigation of Code Library Hallucinations
by: Miranda-Pena, Clarissa, et al.
Published: (2026)

A Survey of using Large Language Models for Generating Infrastructure as Code
by: Srivatsa, Kalahasti Ganesh, et al.
Published: (2024)

Breaking the Cycle of Recurring Failures: Applying Generative AI to Root Cause Analysis in Legacy Banking Systems
by: Jin, Siyuan, et al.
Published: (2024)

LLMs in Mobile Apps: Practices, Challenges, and Opportunities
by: Hau, Kimberly, et al.
Published: (2025)

Bridging AI Innovation and Healthcare Needs: Lessons Learned from Incorporating Modern NLP at The BC Cancer Registry
by: Gondara, Lovedeep, et al.
Published: (2025)

Automated Unity Game Template Generation from GDDs via NLP and Multi-Modal LLMs
by: Hassan, Amna
Published: (2025)

Software-Based Dialogue Systems: Survey, Taxonomy and Challenges
by: Motger, Quim, et al.
Published: (2021)

Firefly: Illuminating Large-Scale Verified Tool-Call Data Generation from Real APIs
by: Lu, Yuxuan, et al.
Published: (2026)

Novel Preprocessing Technique for Data Embedding in Engineering Code Generation Using Large Language Model
by: Lin, Yu-Chen, et al.
Published: (2023)

SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation
by: Ma, Zeyao, et al.
Published: (2024)

Verus-SpecGym: An Agentic Environment for Evaluating Specification Autoformalization
by: Agarwal, Anmol, et al.
Published: (2026)

Contextualized Data-Wrangling Code Generation in Computational Notebooks
by: Huang, Junjie, et al.
Published: (2024)

CallNavi, A Challenge and Empirical Study on LLM Function Calling and Routing
by: Song, Yewei, et al.
Published: (2025)

Generating and Evaluating Sustainable Procurement Criteria for the Swiss Public Sector using In-Context Prompting with Large Language Models
by: Gao, Yingqiang, et al.
Published: (2026)

Is Open Source the Future of AI? A Data-Driven Approach
by: Vake, Domen, et al.
Published: (2025)

Red Teaming Contemporary AI Models: Insights from Spanish and Basque Perspectives
by: Romero-Arjona, Miguel, et al.
Published: (2025)

Nissist: An Incident Mitigation Copilot based on Troubleshooting Guides
by: An, Kaikai, et al.
Published: (2024)

NoFunEval: Funny How Code LMs Falter on Requirements Beyond Functional Correctness
by: Singhal, Manav, et al.
Published: (2024)

SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?
by: Deng, Xiang, et al.
Published: (2025)

Tool-Aware Planning in Contact Center AI: Evaluating LLMs through Lineage-Guided Query Decomposition
by: Nathan, Varun, et al.
Published: (2026)

Seed-Coder: Let the Code Model Curate Data for Itself
by: Seed, ByteDance, et al.
Published: (2025)

LLMs for Science: Usage for Code Generation and Data Analysis
by: Nejjar, Mohamed, et al.
Published: (2023)

SWE-bench Multimodal: Do AI Systems Generalize to Visual Software Domains?
by: Yang, John, et al.
Published: (2024)

Evaluation of Code LLMs on Geospatial Code Generation
by: Gramacki, Piotr, et al.
Published: (2024)

CYCLE: Learning to Self-Refine the Code Generation
by: Ding, Yangruibo, et al.
Published: (2024)

Measuring the Influence of Incorrect Code on Test Generation
by: Huang, Dong, et al.
Published: (2024)

Test Code Generation for Telecom Software Systems using Two-Stage Generative Model
by: Nabeel, Mohamad, et al.
Published: (2024)

Automated Test Data Generation for Enterprise Protobuf Systems: A Metaclass-Enhanced Statistical Approach
by: Du, Y.
Published: (2025)