Tag: cs.SE
arXiv:2602.21251v1 Announce Type: cross Abstract: Legacy JavaScript systems lack type safety, making maintenance risky. While TypeScript can help, manually adding types is expensive. Previous automated …
arXiv:2602.22302v1 Announce Type: new Abstract: Traditional software relies on contracts -- APIs, type systems, assertions -- to specify and enforce correct behavior. AI agents, by …
arXiv:2602.21265v1 Announce Type: new Abstract: We introduce \ToolMATH, a math-grounded benchmark that evaluates tool-augmented language models in realistic multi-tool environments where the output depends on …
arXiv:2602.20610v1 Announce Type: cross Abstract: Specifications are vital for ensuring program correctness, yet writing them manually remains challenging and time-intensive. Recent large language model (LLM)-based …
arXiv:2602.18307v1 Announce Type: cross Abstract: Large language models have achieved striking results in interactive theorem proving, particularly in Lean. However, most benchmarks for LLM-based proof …
arXiv:2602.17697v1 Announce Type: new Abstract: Large Language Models (LLMs) are being increasingly used across a wide range of tasks. However, their substantial computational demands raise …
arXiv:2602.15037v1 Announce Type: cross Abstract: As large language models (LLMs) advance toward expert-level performance in engineering domains, reliable reasoning under user-specified constraints becomes critical. In …
arXiv:2602.15449v1 Announce Type: new Abstract: Large Language Models (LLMs) are changing the coding paradigm, known as vibe coding, yet synthesizing algorithmically sophisticated and robust code …
arXiv:2602.16891v1 Announce Type: new Abstract: Agent development kits (ADKs) provide effective platforms and tooling for constructing agents, and their designs are critical to the constructed …
arXiv:2602.16943v1 Announce Type: new Abstract: Large language models deployed as agents increasingly interact with external systems through tool calls--actions with real-world consequences that text outputs …
arXiv:2602.17084v1 Announce Type: new Abstract: The rapid adoption of large language models has led to the emergence of AI coding agents that autonomously create pull …
arXiv:2602.16819v1 Announce Type: cross Abstract: When assessing the quality of coding agents, predominant benchmarks focus on solving single issues on GitHub, such as SWE-Bench. In …
