3 citations · 3 across the 7 of their papers we have counts for
8 papers
DVAGen: Dynamic Vocabulary Augmented Generation
Wei Du, Nuowei Liu, Jie Wang +4
Language models trained with a fixed vocabulary struggle to generalize to novel or out-of-vocabulary words, limiting their flexibility in handling diverse token combinations. Exist…
PDFBench: A Benchmark for De novo Protein Design from Function
Jiahao Kuang, Nuowei Liu, Jie Wang +3
Function-guided protein design is a crucial task with significant applications in drug discovery and enzyme engineering. However, the field lacks a unified and comprehensive evalua…
Protein Design with Dynamic Protein Vocabulary
Nuowei Liu, Jiahao Kuang, Yanting Liu +4
Protein design is a fundamental challenge in biotechnology, aiming to design novel sequences with specific functions within the vast space of possible proteins. Recent advances in…
The Role of Visual Modality in Multimodal Mathematical Reasoning: Challenges and Insights
Yufang Liu, Yao Du, Tao Ji +6
Recent research has increasingly focused on multimodal mathematical reasoning, particularly emphasizing the creation of relevant datasets and benchmarks. Despite this, the role of…
EvoLlama: Enhancing LLMs' Understanding of Proteins via Multimodal Structure and Sequence Representations
Nuowei Liu, Changzhi Sun, Tao Ji +4
Current Large Language Models (LLMs) for understanding proteins primarily treats amino acid sequences as a text modality. Meanwhile, Protein Language Models (PLMs), such as ESM-2,…
AntLM: Bridging Causal and Masked Language Models
Xinru Yu, Bin Guo, Shiwei Luo +3
Causal Language Modeling (CLM) and Masked Language Modeling (MLM) are two mainstream learning paradigms based on Transformer networks, specifically the Decoder-only and Encoder-onl…
Generation with Dynamic Vocabulary
Yanting Liu, Tao Ji, Changzhi Sun +2
We introduce a new dynamic vocabulary for language models. It can involve arbitrary text spans during generation. These text spans act as basic generation bricks, akin to tokens in…
Investigating and Mitigating Object Hallucinations in Pretrained Vision-Language (CLIP) Models
Yufang Liu, Tao Ji, Changzhi Sun +2
Large Vision-Language Models (LVLMs) have achieved impressive performance, yet research has pointed out a serious issue with object hallucinations within these models. However, the…