6 papers
Regime-Aware Peer Specialization for Robust RAG under Heterogeneous Knowledge Conflicts
Bo Wang, Heyan Huang, Yaolin Li +5
Retrieval-augmented generation (RAG) improves language models by grounding generation in external context. However, it can be fragile when the retrieved context conflicts with the…
EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain
Yi-Fan Lu, Xian-Ling Mao, Bo Wang +2
It is crucial to understand a specific domain by events. Extensive event extraction research has been conducted in many domains such as news, finance, and biology. However, event e…
Retrieved In-Context Principles from Previous Mistakes
Hao Sun, Yong Jiang, Bo Wang +4
In-context learning (ICL) has been instrumental in adapting Large Language Models (LLMs) to downstream tasks using correct input-output examples. Recent advances have attempted to…
AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning
Hao Sun, Jiayi Wu, Hengyi Cai +6
Recent advancements in large language models (LLMs) have been remarkable. Users face a choice between using cloud-based LLMs for generation quality and deploying local-based LLMs f…
Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model
Guoqing Ma, Haoyang Huang, Kun Yan +112
We present Step-Video-T2V, a state-of-the-art text-to-video pre-trained model with 30B parameters and the ability to generate videos up to 204 frames in length. A deep compression…
Towards Verifiable Text Generation with Evolving Memory and Self-Reflection
Hao Sun, Hengyi Cai, Bo Wang +5
Despite the remarkable ability of large language models (LLMs) in language comprehension and generation, they often suffer from producing factually incorrect information, also know…