8 citations · 12 across the 9 of their papers we have counts for
9 papers
MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing
Han Chen, Zining Zhang, Wenqi Pei +6
Memory is a fundamental component for long-context LLM agents, supporting persistent state across interactions through a continuous serve-and-update lifecycle. Despite substantial…
XtraGPT: Context-Aware and Controllable Academic Paper Revision via Human-AI Collaboration
Nuo Chen, Andre Lin HuiKai, Jiaying Wu +5
Despite the growing adoption of large language models (LLMs) in academic workflows, their capabilities remain limited in supporting high-quality scientific writing. Most existing s…
LogQuant: Log-Distributed 2-Bit Quantization of KV Cache with Superior Accuracy Preservation
Han Chen, Zicong Jiang, Zining Zhang +4
We introduce LogQuant, a groundbreaking 2-bit quantization technique for KV Cache in large language model (LLM) inference, delivering substantial memory savings while preserving su…
Feather-SQL: A Lightweight NL2SQL Framework with Dual-Model Collaboration Paradigm for Small Language Models
Wenqi Pei, Hailing Xu, Hengyuan Zhao +5
Natural Language to SQL (NL2SQL) has seen significant advancements with large language models (LLMs). However, these models often depend on closed-source systems and high computati…
Aggressive Post-Training Compression on Extremely Large Language Models
Zining Zhang, Yao Chen, Bingsheng He +1
The increasing size and complexity of Large Language Models (LLMs) pose challenges for their deployment on personal computers and mobile devices. Aggressive post-training model com…
HARL: Hierarchical Adaptive Reinforcement Learning Based Auto Scheduler for Neural Networks
Zining Zhang, Bingsheng He, Zhenjie Zhang
To efficiently perform inference with neural networks, the underlying tensor programs require sufficient tuning efforts before being deployed into production environments. Usually,…
TransMask: A Compact and Fast Speech Separation Model Based on Transformer
Zining Zhang, Bingsheng He, Zhenjie Zhang
Speech separation is an important problem in speech processing, which targets to separate and generate clean speech from a mixed audio containing speech from different speakers. Em…
GAZEV: GAN-Based Zero-Shot Voice Conversion over Non-parallel Speech Corpus
Zining Zhang, Bingsheng He, Zhenjie Zhang
Non-parallel many-to-many voice conversion is recently attract-ing huge research efforts in the speech processing community. A voice conversion system transforms an utterance of a…
X-TaSNet: Robust and Accurate Time-Domain Speaker Extraction Network
Zining Zhang, Bingsheng He, Zhenjie Zhang
Extracting the speech of a target speaker from mixed audios, based on a reference speech from the target speaker, is a challenging yet powerful technology in speech processing. Rec…