6.5k citations · 10.4k across the 118 of their papers we have counts for
126 papers
Towards Unified and Effective Domain Generalization
Yiyuan Zhang, Kaixiong Gong, Xiaohan Ding +4
We propose , a novel and fied framework for omain eneralization that is capable of significantly enhancing the out-of-distribu…
SPEED: Speculative Pipelined Execution for Efficient Decoding
Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh +4
Generative Large Language Models (LLMs) based on the Transformer architecture have recently emerged as a dominant foundation model for a wide range of Natural Language Processing t…
Aligning Large Multimodal Models with Factually Augmented RLHF
Zhiqing Sun, Sheng Shen, Shengcao Cao +9
Large Multimodal Models (LMM) are built across modalities and the misalignment between two modalities can result in "hallucination", generating textual outputs that are not grounde…
QD-BEV : Quantization-aware View-guided Distillation for Multi-view 3D Object Detection
Yifan Zhang, Zhen Dong, Huanrui Yang +6
Multi-view 3D detection based on BEV (bird-eye-view) has recently achieved significant improvements. However, the huge memory consumption of state-of-the-art models makes it hard t…
NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection
Chenfeng Xu, Bichen Wu, Ji Hou +8
We present NeRF-Det, a novel method for indoor 3D detection with posed RGB images as input. Unlike existing indoor 3D detection methods that struggle to model scene geometry, our m…
SqueezeLLM: Dense-and-Sparse Quantization
Sehoon Kim, Coleman Hooper, Amir Gholami +5
Generative Large Language Models (LLMs) have demonstrated remarkable results for a wide range of tasks. However, deploying these models for inference has been a significant challen…