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Shichen Fan

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#natural language process... Preprint May 2026

Beyond Math and Code: Lightweight Corpus-Grounded Process Rewards for Factual Question Answering

CorVer (Corpus Verify) is a lightweight training-time approach to process supervision that derives sentence-level rewards from corpus co-occurrence statistics and outperforms the unmodified models in all standard factual-QA settings.

Shi-Chen Fan, Hao-Chang Hao, De-Hai Min et al. · 5 citations
Preprint Aug 2026

Agentic Commerce World: An Auditable and Verifiable Environment for Vibe Commerce

In vibe coding, people describe software in natural language and delegate implementation to AI agents. By analogy, vibe commerce allows people to express buying or selling goals in natural language and delegate the corresponding tasks to agents. Commerce, however, requires independently controlled Buyer and Merchant ag...

Shichen Fan, Mingdai Yang, Duo Wang et al. · 0 citations
Jul 2026

Paying for Honesty Without Knowing the Truth: Reputation-Penalty Design for LLM Marketplace Agents

It is shown that this felt penalty becomes behaviorally binding through SPARC, a byte-clean code-gated reflection mechanism: LLM merchants fabricate when lying is free but restrain themselves when fabrication costs them sales, a self-interested response rather than compliance.

Mingdai Yang, Shichen Fan, Kejing Yu et al. · 1 citation

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