Papers by Ziyao Chen

3 papers
RealSec-bench: A Benchmark for Evaluating Secure Code Generation in Real-World Repositories (2026.findings-acl)

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Challenge: Existing benchmarks for large language models fail to capture complex interplay between functionality and security.
Approach: They propose a benchmark for secure code generation constructed from real-world, high-risk Java repositories.
Outcome: The proposed benchmarks highlight the gap between functional and secure code generation in LLMs.
Spatiotemporal Sycophancy: Negation-Based Gaslighting in Video Large Language Models (2026.findings-acl)

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Challenge: Existing Vid-LLMs lack robust mechanisms for maintaining grounded spatiotemporal beliefs under conversational feedback.
Approach: They propose a negation-based gaslighting evaluation framework and introduce a benchmark to investigate spatiotemporal sycophancy.
Outcome: The proposed framework evaluates state-of-the-art Vid-LLMs across video understanding tasks.
Token-level Preference Self-Alignment Optimization for Multi-style Outline Controllable Generation (2025.findings-acl)

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Challenge: Existing attempts to outline generation are limited by response pair requirements and substantial computation costs.
Approach: They propose a token-level preference self-alignment optimization for outline controllable generation that extends the Bradley-Terry model from pair-wise to list-wise comparison.
Outcome: The proposed method outperforms existing methods by 19.28% in performance while requiring only 56.25% training time.

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