8 citations · 25 across the 24 of their papers we have counts for
24 papers
: Attention-Aware Accurate KV Cache Fusion for Fast Large Language Model Serving
Yuechi Zhou, Yi Su, Jianxin Zhang +5
Large language models (LLMs) have demonstrated strong capabilities in processing long contexts, enabling them to tackle tasks involving long textual inputs such as multi-turn conve…
Accurate KV Cache Quantization with Outlier Tokens Tracing
Yi Su, Yuechi Zhou, Quantong Qiu +6
The impressive capabilities of Large Language Models (LLMs) come at the cost of substantial computational resources during deployment. While KV Cache can significantly reduce recom…
Alignment-Augmented Speculative Decoding with Alignment Sampling and Conditional Verification
Jikai Wang, Zhenxu Tian, Juntao Li +5
Recent works have revealed the great potential of speculative decoding in accelerating the autoregressive generation process of large language models. The success of these methods…
Taming the Titans: A Survey of Efficient LLM Inference Serving
Ranran Zhen, Juntao Li, Yixin Ji +7
Large Language Models (LLMs) for Generative AI have achieved remarkable progress, evolving into sophisticated and versatile tools widely adopted across various domains and applicat…
Beware of Calibration Data for Pruning Large Language Models
Yixin Ji, Yang Xiang, Juntao Li +5
As large language models (LLMs) are widely applied across various fields, model compression has become increasingly crucial for reducing costs and improving inference efficiency. P…
MSceneSpeech: A Multi-Scene Speech Dataset For Expressive Speech Synthesis
Qian Yang, Jialong Zuo, Zhe Su +6
We introduce an open source high-quality Mandarin TTS dataset MSceneSpeech (Multiple Scene Speech Dataset), which is intended to provide resources for expressive speech synthesis.…
OPT-Tree: Speculative Decoding with Adaptive Draft Tree Structure
Jikai Wang, Yi Su, Juntao Li +5
Autoregressive language models demonstrate excellent performance in various scenarios. However, the inference efficiency is limited by its one-step-one-word generation mode, which…
A General and Flexible Multi-concept Parsing Framework for Multilingual Semantic Matching
Dong Yao
Sentence semantic matching is a research hotspot in natural language processing, which is considerably significant in various key scenarios, such as community question answering, s…
Mirror: A Universal Framework for Various Information Extraction Tasks
Tong Zhu, Junfei Ren, Zijian Yu +7
Sharing knowledge between information extraction tasks has always been a challenge due to the diverse data formats and task variations. Meanwhile, this divergence leads to informat…
How Well Do Large Language Models Understand Syntax? An Evaluation by Asking Natural Language Questions
Houquan Zhou, Yang Hou, Zhenghua Li +4
While recent advancements in large language models (LLMs) bring us closer to achieving artificial general intelligence, the question persists: Do LLMs truly understand language, or…
High-order Joint Constituency and Dependency Parsing
Yanggan Gu, Yang Hou, Zhefeng Wang +2
This work revisits the topic of jointly parsing constituency and dependency trees, i.e., to produce compatible constituency and dependency trees simultaneously for input sentences,…
AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing
Asaad Alghamdi, Xinyu Duan, Wei Jiang +9
Developing monolingual large Pre-trained Language Models (PLMs) is shown to be very successful in handling different tasks in Natural Language Processing (NLP). In this work, we pr…
Reference Matters: Benchmarking Factual Error Correction for Dialogue Summarization with Fine-grained Evaluation Framework
Mingqi Gao, Xiaojun Wan, Jia Su +2
Factuality is important to dialogue summarization. Factual error correction (FEC) of model-generated summaries is one way to improve factuality. Current FEC evaluation that relies…
CopyNE: Better Contextual ASR by Copying Named Entities
Shilin Zhou, Zhenghua Li, Yu Hong +3
End-to-end automatic speech recognition (ASR) systems have made significant progress in general scenarios. However, it remains challenging to transcribe contextual named entities (…
CED: Catalog Extraction from Documents
Tong Zhu, Guoliang Zhang, Zechang Li +7
Sentence-by-sentence information extraction from long documents is an exhausting and error-prone task. As the indicator of document skeleton, catalogs naturally chunk documents int…
A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends
Xiaoye Qu, Yingjie Gu, Qingrong Xia +3
As more and more Arabic texts emerged on the Internet, extracting important information from these Arabic texts is especially useful. As a fundamental technology, Named entity reco…
Distantly-Supervised Named Entity Recognition with Adaptive Teacher Learning and Fine-grained Student Ensemble
Xiaoye Qu, Jun Zeng, Daizong Liu +3
Distantly-Supervised Named Entity Recognition (DS-NER) effectively alleviates the data scarcity problem in NER by automatically generating training samples. Unfortunately, the dist…
Mining Word Boundaries in Speech as Naturally Annotated Word Segmentation Data
Lei Zhang, Zhenghua Li, Shilin Zhou +4
Inspired by early research on exploring naturally annotated data for Chinese word segmentation (CWS), and also by recent research on integration of speech and text processing, this…
Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding
Abbas Ghaddar, Yimeng Wu, Sunyam Bagga +11
There is a growing body of work in recent years to develop pre-trained language models (PLMs) for the Arabic language. This work concerns addressing two major problems in existing…
Delving Deep into Regularity: A Simple but Effective Method for Chinese Named Entity Recognition
Yingjie Gu, Xiaoye Qu, Zhefeng Wang +3
Recent years have witnessed the improving performance of Chinese Named Entity Recognition (NER) from proposing new frameworks or incorporating word lexicons. However, the inner com…
JABER and SABER: Junior and Senior Arabic BERt
Abbas Ghaddar, Yimeng Wu, Ahmad Rashid +10
Language-specific pre-trained models have proven to be more accurate than multilingual ones in a monolingual evaluation setting, Arabic is no exception. However, we found that prev…
Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph
Tong Zhu, Xiaoye Qu, Wenliang Chen +4
Most previous studies of document-level event extraction mainly focus on building argument chains in an autoregressive way, which achieves a certain success but is inefficient in b…
An In-depth Study on Internal Structure of Chinese Words
Chen Gong, Saihao Huang, Houquan Zhou +5
Unlike English letters, Chinese characters have rich and specific meanings. Usually, the meaning of a word can be derived from its constituent characters in some way. Several previ…
Read, Retrospect, Select: An MRC Framework to Short Text Entity Linking
Yingjie Gu, Xiaoye Qu, Zhefeng Wang +3
Entity linking (EL) for the rapidly growing short text (e.g. search queries and news titles) is critical to industrial applications. Most existing approaches relying on adequate co…