activity
20232026
most citedSpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

4 citations · 6 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

InfoVis: Unified Slide Image Generation and Editing

Jiahao Wang, Xiyan Jiang, Chenyuan Wu +7

Generating and editing presentation slides requires models to combine accurate text rendering, instruction following, visual grounding, aesthetic design, and precise editing within…

cs.CL2025

PretrainZero: Reinforcement Active Pretraining

Xingrun Xing, Zhiyuan Fan, Jie Lou +3

Mimicking human behavior to actively learning from general experience and achieve artificial general intelligence has always been a human dream. Recent reinforcement learning (RL)…

cs.CV2025

EditScore: Unlocking Online RL for Image Editing via High-Fidelity Reward Modeling

Xin Luo, Jiahao Wang, Chenyuan Wu +6

Instruction-guided image editing has achieved remarkable progress, yet current models still face challenges with complex instructions and often require multiple samples to produce…

cs.LG2025

EfficientLLM: Scalable Pruning-Aware Pretraining for Architecture-Agnostic Edge Language Models

Xingrun Xing, Zheng Liu, Shitao Xiao +6

Modern large language models (LLMs) driven by scaling laws, achieve intelligence emergency in large model sizes. Recently, the increasing concerns about cloud costs, latency, and p…

cs.LG2024★ 4 cited

SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking

Xingrun Xing, Boyan Gao, Zheng Zhang +5

Recent advancements in large language models (LLMs) with billions of parameters have improved performance in various applications, but their inference processes demand significant…

cs.NE2024★ 1 cited

SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms

Xingrun Xing, Zheng Zhang, Ziyi Ni +6

Towards energy-efficient artificial intelligence similar to the human brain, the bio-inspired spiking neural networks (SNNs) have advantages of biological plausibility, event-drive…

cs.LG2023★ 1 cited

BiPFT: Binary Pre-trained Foundation Transformer with Low-rank Estimation of Binarization Residual Polynomials

Xingrun Xing, Li Du, Xinyuan Wang +4

Pretrained foundation models offer substantial benefits for a wide range of downstream tasks, which can be one of the most potential techniques to access artificial general intelli…