Huacan Wang
Huacan Wang has 3 papers in our library, in 2026, most of them on Reasoning, Bias, fairness & safety, Vision & language; often with Ronghao Chen, Hao Wang, Jingping Liu.
OpenAlex · h-index 0 · 10 works · 0 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 1 time in our library · ⭐ Paper Stars ranking: #11374
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Fields, topics and concepts
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksPsychology · 1 workSocial Psychology · 1 workComputer Vision and Pattern Recognition · 1 work
🧭 Topics 3Research subjects and languages the work is about.Bias, fairness & safety · 1 workReasoning · 1 workVision & language · 1 work
Works by year
2020s
Papers
- KnowMe-Bench: Benchmarking Person Understanding for Lifelong Digital Companions (2026 · 1 citation)
Digital companions meant to support a user for years must do more than recall facts. They need to explain and anticipate behaviour from a person's motivations and values. Current long-term memory benchmarks mostly use chat logs or synthetic histories and mainly test retrieval. KnowMe-Bench instead draws on long… - MirrorQA: Benchmarking Multimodal LLMs on Mirror-Orientation Reasoning (2026)
Multimodal LLMs often confuse left and right when a question concerns a person's or animal's own body. They tend to answer from the viewer's side of the image rather than the subject's. Existing spatial benchmarks (e.g., EmbSpatial-Bench, VSR) define directions from the camera's viewpoint, and pose datasets like COCO… - SafetyMem: Adaptive Jailbreak Defense via Dual-Component Safety Memory (2026)
LLM jailbreak defenses tend to fall into two camps. Methods that change model weights, such as fine-tuning or trained detectors, are costly and slow to adapt. Inference-time filters are flexible, but they start from scratch on every prompt. SafetyMem is a training-free framework that lets a model accumulate defense…
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