2 citations · 4 across the 6 of their papers we have counts for
5 papers · 1 filter
MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning
Yiqing Liang, Jielin Qiu, Wenhao Ding +7
Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as a powerful paradigm for post-training large language models (LLMs), achieving state-of-the-art perform…
Evaluating Durability: Benchmark Insights into Multimodal Watermarking
Jielin Qiu, William Han, Xuandong Zhao +3
With the development of large models, watermarks are increasingly employed to assert copyright, verify authenticity, or monitor content distribution. As applications become more mu…
Entity6K: A Large Open-Domain Evaluation Dataset for Real-World Entity Recognition
Jielin Qiu, William Han, Winfred Wang +6
Open-domain real-world entity recognition is essential yet challenging, involving identifying various entities in diverse environments. The lack of a suitable evaluation dataset ha…
SnapNTell: Enhancing Entity-Centric Visual Question Answering with Retrieval Augmented Multimodal LLM
Jielin Qiu, Andrea Madotto, Zhaojiang Lin +7
Vision-extended LLMs have made significant strides in Visual Question Answering (VQA). Despite these advancements, VLLMs still encounter substantial difficulties in handling querie…
MMSum: A Dataset for Multimodal Summarization and Thumbnail Generation of Videos
Jielin Qiu, Jiacheng Zhu, William Han +9
Multimodal summarization with multimodal output (MSMO) has emerged as a promising research direction. Nonetheless, numerous limitations exist within existing public MSMO datasets,…