Demo Data from SIGIR 2026 / reviewers in the wild / expert
Yuhao Zhou 0006
dblp:121/6722-6
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2026
0009-0003-6895-6308ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1 · 1 first-author · 1 since 2021Theory of computation · 1 · 1 first-author · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Program verification · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Program verification › proof assistants
proof automation |
1.0 | 1 | 2026 | Towards Language Model Guided TLA+ Proof Automation · FM (1) 2026 |
Program verification
theorem proving |
1.0 | 1 | 2026 | Towards Language Model Guided TLA+ Proof Automation · FM (1) 2026 |
Methods — techniques the papers use, named apart from their topics
symbolic prover · 1.0prompt-based generation · 1.0large language model · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Towards Language Model Guided TLA+ Proof AutomationabstractAbstract Formal theorem proving with $$\texttt {TLA}^{+}$$ TLA + provides rigorous guarantees for system specifications, but constructing proofs requires substantial expertise and effort. While large language models have shown promise in automating proofs for tactic-based theorem provers like Lean, applying these approaches directly to $$\texttt {TLA}^{+}$$ TLA + faces significant challenges due to the hierarchical proof structure of the $$\texttt {TLA}^{+}$$ TLA + proof system. We present a prompt-based approach that leverages LLMs to guide hierarchical decomposition of complex proof obligations into simpler sub-claims, while relying on symbolic provers for verification. Our key insight is to constrain LLMs to generate normalized claim decompositions rather than complete proofs, significantly reducing syntax errors. We also introduce a benchmark suite of 119 theorems adapted from (1) established mathematical collections and (2) inductive proofs of distributed protocols. Our approach consistently outperforms baseline methods across the benchmark suite. Yuhao Zhou 0006, Stavros Tripakis |
FM (1) | 1 |