Large language models equipped with development environments have moved code generation toward repository-scale construction, yet building complete repositories remains difficult because interacting modules, interfaces, configurations, tests, and dependencies must work together. We introduce Code Primitives, agent-nati...
Hai-Bo Jin, Peng Kuang, Xu-Chen Yu et al.· 0 citations
This work organizes 82 reusable methods from Putnam 2000-2014 as Method Contracts, which pair applicability descriptions with Mathlib anchors, a checked example or scaffold, and expected proof obligations, and analyzes when similarity-based representations cannot distinguish methods with different applicability, how er...
Xiao-Peng Yuan, Sui-Jin Wang, Yan-Lin Wang et al.· 0 citations
Large language models (LLMs) equipped with terminal access have demonstrated strong capabilities in automating software engineering tasks. However, existing agents remain brittle on long-horizon workflows, where they must repeatedly reconstruct program state scattered across source files, configurations, tests, depende...
Hai-Bo Jin, Xin-Jie Li, Peng Kuang et al.· 0 citations
Agent harnesses govern how large language models (LLMs) gather context, invoke tools, verify results, preserve state, and terminate, largely affecting agent performance. However, the value of each harness mechanism can differ across heterogeneous tasks: a mechanism that improves one task may impose overhead or context...
Peng Kuang, Hai-Bo Jin, De-Hao Wu et al.· 0 citations
ANTMAN is introduced, an adaptive coordination framework that treats evolving unresolved information needs as the unit of runtime coordination and maintains a revisable Need Graph that tracks unresolved requirements, accumulated evidence, prior attempts, and search progress.
Jerry Wang, Hai-Bo Jin, Xiao-Peng Yuan et al.· 0 citations
STEVE, a stabilization framework with two coupled mechanisms that reduces degradation and produces more robust prompts, provides a practical way to improve the stability and effectiveness of textual-gradient prompt optimization.
Yi-Fan Xu, Yi-Xuan Li, Xin-Zhuo Li et al.· 0 citations
The results indicate that typed state transitions and deterministic evidence control contribute beyond fluent generation alone on quantum-acceleration hypotheses beyond fluent generation alone.
Yijing Zuo, Zhengkang Fu, Zihan Nie et al.· 0 citations
This work introduces Tool Primitives, a design that replaces rigid API schema-based invocation with natural language as the interface for tool calling, where each tool is wrapped with an LLM interface that handles schema resolution and execution internally, enabling natural inter-tool communication for nested and multi...
Hai-Bo Jin, Sui-Jin Wang, Xu-Chen Yu et al.· 2 citations
A synthetic player population is constructed whose traits are ground truth by construction, and an opportunity-aware decision-moment representation is introduced that disentangles preference from the chance to express it; ablating it selectively degrades opportunity-dependent traits.