6 papers · 1 filter
IQuest-Q1: Advancing Foundation Capabilities for Agentic CLI Systems
A. Jian Yang, An Huang, Bo Dan +173
We present IQuest-Q1, a sparse Mixture-of-Experts (MoE) agentic foundation model with 320B total parameters (15B activated). IQuest-Q1 is developed through a three-stage process: (…
GHOST: Geometry-Hierarchical Online Streaming Token Eviction for Efficient 3D Reconstruction
Leyang Chen, Junyi Wu, Zhiteng Li +1
Streaming 3D reconstruction from long monocular video sequences requires maintaining a key-value (KV) cache that grows linearly with sequence length, creating a severe memory bottl…
SOAR: Scale Optimization for Accurate Reconstruction in NVFP4 Quantization
Chengzhu Bao, Xianglong Yan, Zhiteng Li +3
NVFP4 has recently emerged as an efficient 4-bit microscaling format for large language models (LLMs), offering superior numerical fidelity with native hardware support. However, e…
FlashClear: Ultra-Fast Image Content Removal via Efficient Step Distillation and Feature Caching
Yixin Tang, Jiawei Guo, Junxian Li +6
Recently, diffusion-based object removal models have achieved impressive results in eliminating objects and their associated visual effects. However, they indiscriminately denoise…
DQuant: Accurate Low-bit Post-Training Weight Quantization for LLMs
Xianglong Yan, ChengZhu Bao, Zhiteng Li +5
Large language models (LLMs) deliver strong performance, but their high compute and memory costs make deployment difficult in resource-constrained scenarios. Weight-only post-train…
VEQ: Modality-Adaptive Quantization for MoE Vision-Language Models
Guangshuo Qin, Zhiteng Li, Zheng Chen +3
Mixture-of-Experts(MoE) Vision-Language Models (VLMs) offer remarkable performance but incur prohibitive memory and computational costs, making compression essential. Post-Training…