40 citations · 100 across the 68 of their papers we have counts for
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cs.AI2026
Repairing LLM-Generated Specifications with Deterministic Diagnosis
Giovanni Vaccarino, Emanuele La Malfa, Dehai Min +6
Large language models (LLMs) are increasingly used as formalizers: given a reasoning problem expressed in natural language, they produce a formal specification that a symbolic solv…
cs.AI2026
Escaping Reasoning Basin Collapse with History-Biased Search
Lu Cheng
Inference-time search with large language models (LLMs) often concentrates on a small set of structurally or semantically similar trajectories, leaving alternative reasoning strate…
cs.AI2026
A Novel Multi-Agent Architecture to Reduce Hallucinations of Large Language Models in Multi-Step Structural Modeling
Ziheng Geng, Jiachen Liu, Ran Cao +3
Large language models (LLMs) such as GPT and Gemini have demonstrated remarkable capabilities in contextual understanding and reasoning. The strong performance of LLMs has sparked…