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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.SE2026

Instruction Alignment for Binary Code Representation Learning

Huaijin Wang, Shuai Wang

Binary code representation learning is a fundamental problem in software security and reverse engineering. Existing methods mainly learn function-level embeddings that capture coar…

cs.SE2026

KQFuzz: Knowledge-Guided Fuzzing for Quantum Libraries via Large Language Models

Fuyuan Xia, Qixin Zhang, Chenhao Ying +5

The paper introduces KQFuzz, a knowledge-guided fuzzing framework that uses large language models to generate and mutate test programs for quantum libraries, achieving higher cover…

cs.CR2026

ZK-Value: A Practical Zero-Knowledge System for Verifiable Data Valuation

Zhaoyu Wang, Pingchuan Ma, Zhantong Xue +4

Data valuation is a foundational task in data marketplaces, where a Shapley-value attribution determines how a buyer's payment is distributed among data providers. Typically, the m…

cs.SE2026

From Evaluation to Enhancement: Large Language Models for Zero-Knowledge Proof Code Generation

Zhantong Xue, Pingchuan Ma, Zhaoyu Wang +4

Zero-knowledge proofs (ZKPs) are increasingly deployed in domains such as privacy-preserving authentication, verifiable computation, and secure finance. However, authoring ZK progr…

cs.LG2026

Efficient Differentiable Causal Discovery via Reliable Super-Structure Learning

Pingchuan Ma, Qixin Zhang, Shuai Wang +1

Recently, differentiable causal discovery has emerged as a promising approach to improve the accuracy and efficiency of existing methods. However, when applied to high-dimensional…

cs.SE2025

Digging Into the Internal: Causality-Based Analysis of LLM Function Calling

Zhenlan Ji, Daoyuan Wu, Wenxuan Wang +3

Function calling (FC) has emerged as a powerful technique for facilitating large language models (LLMs) to interact with external systems and perform structured tasks. However, the…