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20212026
most citedData-Driven Abductive Inference of Library Specifications

15 citations · 24 across the 11 of their papers we have counts for

collaborators

12 papers

cs.AI2026

A Near-Zero Monitor Readout Is Not Evidence of Behavioral Control

Zhe Zhou, Tianhua Tao

Post-training with verifiable rewards can induce reward hacking, motivating the use of monitors within the training objective rather than solely for offline auditing. We show that…

cs.PL2026★ 1 cited

Trace-Guided Synthesis of Effectful Test Generators

Zhe Zhou, Ankush Desai, Benjamin Delaware +1

Several recently proposed program logics have incorporated notions of underapproximation into their design, enabling them to reason about reachability rather than safety. In this p…

cs.CL2026

CharacterFlywheel: Scaling Iterative Improvement of Engaging and Steerable LLMs in Production

Yixin Nie, Lin Guan, Zhongyao Ma +19

This report presents CharacterFlywheel, an iterative flywheel process for improving large language models (LLMs) in production social chat applications across Instagram, WhatsApp,…

cs.AI2026

SWE-Hub: A Unified Production System for Scalable, Executable Software Engineering Tasks

Yucheng Zeng, Shupeng Li, Daxiang Dong +11

Progress in software-engineering agents is increasingly constrained by the scarcity of executable, scalable, and realistic data for training and evaluation. This scarcity stems fro…

cs.AI2026

LOGIGEN: Logic-Driven Generation of Verifiable Agentic Tasks

Yucheng Zeng, Weipeng Lu, Linyun Liu +9

The evolution of Large Language Models (LLMs) from static instruction-followers to autonomous agents necessitates operating within complex, stateful environments to achieve precise…

cs.SE2025

Adaptive Proof Refinement with LLM-Guided Strategy Selection

Minghai Lu, Zhe Zhou, Danning Xie +3

Formal verification via theorem proving enables the expressive specification and rigorous proof of software correctness, but it is difficult to scale due to the significant manual…

cs.PL2025

From Traces to Program Incorrectness: A Type-Theoretic Approach

Yongwei Yuan, Zhe Zhou, Julia Belyakova +2

We present a type-theoretic framework for reasoning about incorrectness in functional programs that interact with effectful, opaque library APIs. Our approach centers on traces --…

cs.PL2025

Type-Based Incorrectness Reasoning

Zhe Zhou, Benjamin Delaware, Suresh Jagannathan

A coverage type generalizes refinement types found in many functional languages with support for must-style underapproximate reasoning. Property-based testing frameworks are one pa…

cs.PL2025★ 1 cited

We've Got You Covered: Type-Guided Repair of Incomplete Input Generators

Patrick LaFontaine, Zhe Zhou, Ashish Mishra +2

Property-based testing (PBT) is a popular technique for automatically testing semantic properties of a program, specified as a pair of pre- and post-conditions. The efficacy of thi…

cs.PL2024★ 1 cited

Derivative-Guided Symbolic Execution

Yongwei Yuan, Zhe Zhou, Julia Belyakova +1

We consider the formulation of a symbolic execution (SE) procedure for functional programs that interact with effectful, opaque libraries. Our procedure allows specifications of li…

cs.PL2024★ 6 cited

A HAT Trick: Automatically Verifying Representation Invariants Using Symbolic Finite Automata

Zhe Zhou, Qianchuan Ye, Benjamin Delaware +1

Functional programs typically interact with stateful libraries that hide state behind typed abstractions. One particularly important class of applications are data structure implem…

cs.PL2021★ 15 cited

Data-Driven Abductive Inference of Library Specifications

Zhe Zhou, Robert Dickerson, Benjamin Delaware +1

Programmers often leverage data structure libraries that provide useful and reusable abstractions. Modular verification of programs that make use of these libraries naturally rely…