9 papers
FlashRT: Towards Computationally and Memory Efficient Red-Teaming for Prompt Injection and Knowledge Corruption
Yanting Wang, Chenlong Yin, Ying Chen +1
Long-context large language models (LLMs)-for example, Gemini-3.1-Pro and Qwen-3.5-are widely used to empower many real-world applications, such as retrieval-augmented generation,…
Ragged Paged Attention: A High-Performance and Flexible LLM Inference Kernel for TPU
Jevin Jiang, Ying Chen, Blake A. Hechtman +2
Large Language Model (LLM) deployment is increasingly shifting to cost-efficient accelerators like Google's Tensor Processing Units (TPUs), prioritizing both performance and total…
Seedance 2.0: Advancing Video Generation for World Complexity
Team Seedance, De Chen, Liyang Chen +168
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…
NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results
Xin Li, Jiachao Gong, Xijun Wang +75
This paper presents an overview of the NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models. This challenge utilizes a new short-form UGC (S-…
PIArena: A Platform for Prompt Injection Evaluation
Runpeng Geng, Chenlong Yin, Yanting Wang +2
Prompt injection attacks pose serious security risks across a wide range of real-world applications. While receiving increasing attention, the community faces a critical gap: the l…
PISanitizer: Preventing Prompt Injection to Long-Context LLMs via Prompt Sanitization
Runpeng Geng, Yanting Wang, Chenlong Yin +3
Long context LLMs are vulnerable to prompt injection, where an attacker can inject an instruction in a long context to induce an LLM to generate an attacker-desired output. Existin…
PIShield: Detecting Prompt Injection Attacks via Intrinsic LLM Features
Wei Zou, Yupei Liu, Yanting Wang +3
LLM-integrated applications are vulnerable to prompt injection attacks, where an attacker contaminates the input to inject malicious instructions, causing the LLM to follow the att…
UniC-RAG: Universal Knowledge Corruption Attacks to Retrieval-Augmented Generation
Runpeng Geng, Yanting Wang, Ying Chen +1
Retrieval-augmented generation (RAG) systems are widely deployed in real-world applications in diverse domains such as finance, healthcare, and cybersecurity. However, many studies…
AttnTrace: Contextual Attribution of Prompt Injection and Knowledge Corruption
Yanting Wang, Runpeng Geng, Ying Chen +1
Long-context large language models (LLMs), such as Gemini-2.5-Pro and Claude-Sonnet-4, are increasingly used to empower advanced AI systems, including retrieval-augmented generatio…