6 citations · 7 across the 4 of their papers we have counts for
5 papers
One Latent, Many Tokens: Jointly Learning Compressed Embeddings for Efficient Language Diffusion
Yulin Yuan, Ying Zhang, Xiangming Meng
Most continuous diffusion language models process one latent position per token at each sampling step, making generation expensive. Two-stage methods lower the cost by reducing the…
Visual-Redundancy-Controlled Parallel Decoding for Diffusion-Based Multimodal Large Language Models
Yulin Yuan, Hongshuo Zhao, Xiangming Meng
Diffusion-based multimodal large language models (dMLLMs) decode by iteratively predicting tokens at multiple masked positions in parallel. This turns each decoding step into a pos…
Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation
Longyue Wang, Siyou Liu, Chenyang Lyu +11
Following last year, we have continued to host the WMT translation shared task this year, the second edition of the Discourse-Level Literary Translation. We focus on three language…
(Perhaps) Beyond Human Translation: Harnessing Multi-Agent Collaboration for Translating Ultra-Long Literary Texts
Minghao Wu, Jiahao Xu, Yulin Yuan +4
Literary translation remains one of the most challenging frontiers in machine translation due to the complexity of capturing figurative language, cultural nuances, and unique styli…
Findings of the WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in the Cosmos of LLMs
Longyue Wang, Zhaopeng Tu, Yan Gu +14
Translating literary works has perennially stood as an elusive dream in machine translation (MT), a journey steeped in intricate challenges. To foster progress in this domain, we h…