Papers by Yangguang Shao

2 papers
R2F: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference (2022.emnlp-main)

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Challenge: Document-level natural language inference (DOCNLI) is a new task in natural language processing.
Approach: They propose a document-level natural language inference framework that fuses sentence-level tasks into a set of sentence-based tasks.
Outcome: The proposed framework improves interpretability and performance with evidence.
SecureWebArena: A Holistic Security Evaluation Benchmark for LVLM-based Web Agents (2026.findings-acl)

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Challenge: Existing security benchmarks only cover user-level prompts and environmental threats . however, these models are vulnerable to pop-up attacks and prompt injections .
Approach: They propose a security benchmark that covers a set of six attack vectors that span both user-level and environment-level manipulations.
Outcome: The proposed security benchmarks cover a set of six real-world web environments with 2,970 adversarial trajectories and a multi-layered evaluation protocol dissecting agent failures across internal reasoning, behavioral execution, and task outcomes.

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