Coding papers

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20 papers found

ReviewPaperPublishedTopics

7.0Code2UML: Agentic LLMs with context engineering for scalable software visualizationThis work addresses the challenge of scaling LLM-based code analysis to large codebases, which is crucial for automating software documentation and improving developer productivity.May 26, 2026LLM Agent Coding

6.8Understanding Conversational Patterns in Multi-agent Programming: A Case Study on Fibonacci Game DevelopmentUnderstanding how LLM-based agents can effectively collaborate in software engineering tasks is crucial for developing autonomous systems that can reliably produce correct solutions.May 26, 2026LLM Agent Coding

7.8Autonomous Intelligent Agents for Natural-Language-Driven Web Execution with Integrated Security AssuranceThis work addresses critical challenges in web testing and security, providing a practical solution that can save developers time and improve software reliability.May 18, 2026Agent Security Coding

7.5OMAC: A Holistic Optimization Framework for LLM-Based Multi-Agent CollaborationThis work addresses a gap in the systematic design and optimization of LLM-based multi-agent systems, which is crucial for enhancing their performance in complex tasks.May 16, 2026LLM Agent Reasoning

7.2Distribution-Aware Algorithm Design with LLM AgentsThis research could lead to more efficient algorithm design by leveraging LLMs to tailor solver code to specific distributions, potentially reducing computational costs and improving performance in practical applications.May 16, 2026LLM Agent Coding

6.8Agentic Interpretation: Lattice-Structured Evidence for LLM-Based Program AnalysisThis framework could improve program analysis by leveraging LLMs to incorporate dynamic information sources, potentially leading to more accurate and comprehensive analyses.May 14, 2026LLM Reasoning Coding

7.2M2A: Synergizing Mathematical and Agentic Reasoning in Large Language ModelsThis work is relevant for AI researchers and engineers interested in improving the reasoning capabilities of language models, particularly in applications requiring both mathematical and interactive reasoning.May 13, 2026LLM Agent Reasoning

7.0Reasoning Is Not Free: Robust Adaptive Cost-Efficient Routing for LLM-as-a-JudgeUnderstanding when and how to leverage reasoning in LLMs can lead to more efficient and accurate automated decision-making systems, which is crucial for applications requiring structured verification.May 13, 2026LLM Reasoning Evaluation

7.2ReaComp: Compiling LLM Reasoning into Symbolic Solvers for Efficient Program SynthesisThis work is relevant for AI researchers and engineers interested in improving the efficiency and reliability of program synthesis by reducing dependency on LLMs during inference, thus saving computational resources and potentially broadening the applicability of AI solutions.May 8, 2026LLM Reasoning Coding

7.5Evaluating Prompting and Execution-Based Methods for Deterministic Computation in LLMsUnderstanding the capabilities and limitations of LLMs in deterministic tasks is crucial for researchers and engineers aiming to integrate these models into reliable computational applications.May 8, 2026LLM Evaluation Coding

7.2ProgramBench: Can Language Models Rebuild Programs From Scratch?This research addresses a significant gap in evaluating language models for software development, moving beyond simple tasks to more complex, real-world scenarios.May 7, 2026LLM Agent Evaluation

6.8AI Alignment via Incentives and CorrectionUnderstanding and improving AI alignment is crucial for ensuring that AI systems behave as intended, especially as they become more autonomous and integrated into critical applications.May 6, 2026Alignment Agent Coding

7.2LLMs as ASP Programmers: Self-Correction Enables Task-Agnostic Nonmonotonic ReasoningThis approach could enhance the reasoning capabilities of LLMs by allowing them to handle nonmonotonic tasks more effectively, potentially broadening their applicability in complex problem-solving scenarios.May 1, 2026LLM Reasoning Coding

7.2IACDM: Interactive Adversarial Convergence Development Methodology -- A Structured Framework for AI-Assisted Software DevelopmentAs AI tools become more prevalent in software development, understanding and addressing their limitations is crucial for ensuring the reliability and security of AI-generated applications.May 1, 2026Coding Security Evaluation

7.2Understanding the Limits of Automated Evaluation for Code Review Bots in PracticeUnderstanding the limitations of automated code review tools is crucial for improving their design and integration into software development workflows.Apr 29, 2026Evaluation Coding

6.8An Empirical Evaluation of Locally Deployed LLMs for Bug Detection in Python CodeUnderstanding the capabilities of locally deployed LLMs for bug detection is crucial for privacy-sensitive and resource-constrained environments, offering insights into their practical applicability and limitations.Apr 29, 2026LLM Evaluation Coding

6.8Focus Session: Hardware and Software Techniques for Accelerating Multimodal Foundation ModelsThis work is relevant for AI engineers and researchers looking to improve the efficiency and performance of multimodal foundation models, which are increasingly used in diverse applications.Apr 27, 2026Multimodal Infra Architecture

7.2Shift-Up: A Framework for Software Engineering Guardrails in AI-native Software Development -- Initial FindingsAs generative AI transforms software engineering, establishing effective frameworks like Shift-Up is crucial for maintaining code quality and project sustainability.Apr 23, 2026Coding Architecture

7.2From Feelings to Metrics: Understanding and Formalizing How Users Vibe-Test LLMsUnderstanding and formalizing user evaluation practices can bridge the gap between benchmark scores and real-world applicability, making LLM assessments more relevant.Apr 18, 2026Other

7.5AgentForge: Execution-Grounded Multi-Agent LLM Framework for Autonomous Software EngineeringThis framework addresses the critical gap in verifying the correctness of code generated by large language models, making it highly relevant for developers and researchers focused on reliable software automation.Apr 17, 2026LLM Agent Coding