activity
20242026
most citedEfficient Prompting Methods for Large Language Models: A Survey

18 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

eess.AS2026

VibeVoice-ASR-Streaming Technical Report

Yujie Tu, Zhiliang Peng, Jianwei Yu +11

Traditional speaker-attributed ASR systems treated ASR and speaker diarization as two separate tasks. Recently, end-to-end models such as VibeVoice-ASR have unified the two tasks w…

cs.SD2026

VibeVoice-ASR-BitNet Technical Report

Songchen Xu, Ting Song, Shaohan Huang +10

We present VibeVoice-ASR-BitNet, a compressed variant of VibeVoice-ASR optimized for real-time inference on edge CPUs. We apply heterogeneous quantization tailored to the computati…

cs.LG2026

SlideSparse: Fast and Flexible (2N-2):2N Structured Sparsity

Hanyong Shao, Yingbo Hao, Ting Song +10

NVIDIA's 2:4 Sparse Tensor Cores deliver 2x throughput but demand strict 50% pruning -- a ratio that collapses LLM reasoning accuracy (Qwen3: 54% to 15%). Milder patter…

cs.SD2026

VIBEVOICE-ASR Technical Report

Zhiliang Peng, Jianwei Yu, Yaoyao Chang +21

This report presents VibeVoice-ASR, a general-purpose speech understanding framework built upon VibeVoice, designed to address the persistent challenges of context fragmentation an…

cs.LG2025

DConAD: A Differencing-based Contrastive Representation Learning Framework for Time Series Anomaly Detection

Wenxin Zhang, Xiaojian Lin, Wenjun Yu +7

Time series anomaly detection holds notable importance for risk identification and fault detection across diverse application domains. Unsupervised learning methods have become pop…

cs.CL2024★ 18 cited

Efficient Prompting Methods for Large Language Models: A Survey

Kaiyan Chang, Songcheng Xu, Chenglong Wang +4

Prompting is a mainstream paradigm for adapting large language models to specific natural language processing tasks without modifying internal parameters. Therefore, detailed suppl…