65 citations · 65 across the 6 of their papers we have counts for
7 papers
ReGLA: Efficient Receptive-Field Modeling with Gated Linear Attention Network
Junzhou Li, Manqi Zhao, Yilin Gao +4
Balancing accuracy and latency on high-resolution images is a critical challenge for lightweight models, particularly for Transformer-based architectures that often suffer from exc…
DART: Diffusion-Inspired Speculative Decoding for Fast LLM Inference
Fuliang Liu, Xue Li, Ketai Zhao +7
Speculative decoding is an effective and lossless approach for accelerating LLM inference. However, existing widely adopted model-based draft designs, such as EAGLE3, improve accur…
Bridging the Knowledge-Action Gap by Evaluating LLMs in Dynamic Dental Clinical Scenarios
Hongyang Ma, Tiantian Gu, Huaiyuan Sun +9
The transition of Large Language Models (LLMs) from passive knowledge retrievers to autonomous clinical agents demands a shift in evaluation-from static accuracy to dynamic behavio…
Forging a Dynamic Memory: Retrieval-Guided Continual Learning for Generalist Medical Foundation Models
Zizhi Chen, Yizhen Gao, Minghao Han +4
Multimodal biomedical Vision-Language Models (VLMs) exhibit immense potential in the field of Continual Learning (CL). However, they confront a core dilemma: how to preserve fine-g…
Assay2Mol: large language model-based drug design using BioAssay context
Yifan Deng, Spencer S. Ericksen, Anthony Gitter
Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…
DeepMath-Creative: A Benchmark for Evaluating Mathematical Creativity of Large Language Models
Xiaoyang Chen, Xinan Dai, Yu Du +28
To advance the mathematical proficiency of large language models (LLMs), the DeepMath team has launched an open-source initiative aimed at developing an open mathematical LLM and s…