1 citations · 2 across the 6 of their papers we have counts for
6 papers
Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA
Lifeng Qiao, Peng Ye, Yuchen Ren +5
Foundation models have made significant strides in understanding the genomic language of DNA sequences. However, previous models typically adopt the tokenization methods designed f…
PRANCE: Joint Token-Optimization and Structural Channel-Pruning for Adaptive ViT Inference
Ye Li, Chen Tang, Yuan Meng +5
We introduce PRANCE, a Vision Transformer compression framework that jointly optimizes the activated channels and reduces tokens, based on the characteristics of inputs. Specifical…
Evaluating the Generalization Ability of Quantized LLMs: Benchmark, Analysis, and Toolbox
Yijun Liu, Yuan Meng, Fang Wu +7
Large language models (LLMs) have exhibited exciting progress in multiple scenarios, while the huge computational demands hinder their deployments in lots of real-world application…
TMPQ-DM: Joint Timestep Reduction and Quantization Precision Selection for Efficient Diffusion Models
Haojun Sun, Chen Tang, Zhi Wang +4
Diffusion models have emerged as preeminent contenders in the realm of generative models. Distinguished by their distinctive sequential generative processes, characterized by hundr…
Towards Fair and Comprehensive Comparisons for Image-Based 3D Object Detection
Xinzhu Ma, Yongtao Wang, Yinmin Zhang +5
In this work, we build a modular-designed codebase, formulate strong training recipes, design an error diagnosis toolbox, and discuss current methods for image-based 3D object dete…
An Empirical Study of Pseudo-Labeling for Image-based 3D Object Detection
Xinzhu Ma, Yuan Meng, Yinmin Zhang +4
Image-based 3D detection is an indispensable component of the perception system for autonomous driving. However, it still suffers from the unsatisfying performance, one of the main…