150 citations · 415 across the 37 of their papers we have counts for
37 papers
ProAgent: Building Proactive Cooperative Agents with Large Language Models
Ceyao Zhang, Kaijie Yang, Siyi Hu +12
Building agents with adaptive behavior in cooperative tasks stands as a paramount goal in the realm of multi-agent systems. Current approaches to developing cooperative agents rely…
A Dataflow Compiler for Efficient LLM Inference using Custom Microscaling Formats
Jianyi Cheng, Cheng Zhang, Zhewen Yu +3
Model quantization represents both parameters (weights) and intermediate values (activations) in a more compact format, thereby directly reducing both computational and memory cost…
Causal Reinforcement Learning: A Survey
Zhihong Deng, Jing Jiang, Guodong Long +1
Reinforcement learning is an essential paradigm for solving sequential decision problems under uncertainty. Despite many remarkable achievements in recent decades, applying reinfor…
Nonparametric Iterative Machine Teaching
Chen Zhang, Xiaofeng Cao, Weiyang Liu +2
In this paper, we consider the problem of Iterative Machine Teaching (IMT), where the teacher provides examples to the learner iteratively such that the learner can achieve fast co…
Temporal-spatial Correlation Attention Network for Clinical Data Analysis in Intensive Care Unit
Weizhi Nie, Yuhe Yu, Chen Zhang +3
In recent years, medical information technology has made it possible for electronic health record (EHR) to store fairly complete clinical data. This has brought health care into th…
One for All: Unified Workload Prediction for Dynamic Multi-tenant Edge Cloud Platforms
Shaoyuan Huang, Zheng Wang, Heng Zhang +3
Workload prediction in multi-tenant edge cloud platforms (MT-ECP) is vital for efficient application deployment and resource provisioning. However, the heterogeneous application pa…
Improving the Robustness of Summarization Systems with Dual Augmentation
Xiuying Chen, Guodong Long, Chongyang Tao +4
A robust summarization system should be able to capture the gist of the document, regardless of the specific word choices or noise in the input. In this work, we first explore the…
Task-agnostic Distillation of Encoder-Decoder Language Models
Chen Zhang, Yang Yang, Jingang Wang +1
Finetuning pretrained language models (LMs) have enabled appealing performance on a diverse array of tasks. The intriguing task-agnostic property has driven a shifted focus from ta…
Lifting the Curse of Capacity Gap in Distilling Language Models
Chen Zhang, Yang Yang, Jiahao Liu +4
Pretrained language models (LMs) have shown compelling performance on various downstream tasks, but unfortunately they require a tremendous amount of inference compute. Knowledge d…
Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020-2022
Cheng Zhang, Nilam Nur Amir Sjarif, Roslina Ibrahim
Accurately predicting the prices of financial time series is essential and challenging for the financial sector. Owing to recent advancements in deep learning techniques, deep lear…
OliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization
Cong Guo, Jiaming Tang, Weiming Hu +6
Transformer-based large language models (LLMs) have achieved great success with the growing model size. LLMs' size grows by every two years, which outpaces the hardware…
Modular Retrieval for Generalization and Interpretation
Juhao Liang, Chen Zhang, Zhengyang Tang +3
New retrieval tasks have always been emerging, thus urging the development of new retrieval models. However, instantiating a retrieval model for each new retrieval task is resource…
One-shot Machine Teaching: Cost Very Few Examples to Converge Faster
Chen Zhang, Xiaofeng Cao, Yi Chang +1
Artificial intelligence is to teach machines to take actions like humans. To achieve intelligent teaching, the machine learning community becomes to think about a promising topic n…
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise
Wenbo Gong, Joel Jennings, Cheng Zhang +1
Discovering causal relationships between different variables from time series data has been a long-standing challenge for many domains such as climate science, finance, and healthc…
Sparse Teachers Can Be Dense with Knowledge
Yi Yang, Chen Zhang, Dawei Song
Recent advances in distilling pretrained language models have discovered that, besides the expressiveness of knowledge, the student-friendliness should be taken into consideration…
XPrompt: Exploring the Extreme of Prompt Tuning
Fang Ma, Chen Zhang, Lei Ren +5
Prompt tuning learns soft prompts to condition frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner. While prompt tuning has gr…
Nesting Forward Automatic Differentiation for Memory-Efficient Deep Neural Network Training
Cong Guo, Yuxian Qiu, Jingwen Leng +6
An activation function is an element-wise mathematical function and plays a crucial role in deep neural networks (DNN). Many novel and sophisticated activation functions have been…
Structural Bias for Aspect Sentiment Triplet Extraction
Chen Zhang, Lei Ren, Fang Ma +3
Structural bias has recently been exploited for aspect sentiment triplet extraction (ASTE) and led to improved performance. On the other hand, it is recognized that explicitly inco…
Learn the Time to Learn: Replay Scheduling in Continual Learning
Marcus Klasson, Hedvig Kjellström, Cheng Zhang
Replay methods are known to be successful at mitigating catastrophic forgetting in continual learning scenarios despite having limited access to historical data. However, storing h…
ANT: Exploiting Adaptive Numerical Data Type for Low-bit Deep Neural Network Quantization
Cong Guo, Chen Zhang, Jingwen Leng +5
Quantization is a technique to reduce the computation and memory cost of DNN models, which are getting increasingly large. Existing quantization solutions use fixed-point integer o…
LCSM: A Lightweight Complex Spectral Mapping Framework for Stereophonic Acoustic Echo Cancellation
Chenggang Zhang, Jinjiang Liu, Xueliang Zhang
The traditional adaptive algorithms will face the non-uniqueness problem when dealing with stereophonic acoustic echo cancellation (SAEC). In this paper, we first propose an effici…
Aspect-specific Context Modeling for Aspect-based Sentiment Analysis
Fang Ma, Chen Zhang, Bo Zhang +1
Aspect-based sentiment analysis (ABSA) aims at predicting sentiment polarity (SC) or extracting opinion span (OE) expressed towards a given aspect. Previous work in ABSA mostly rel…
Doge Tickets: Uncovering Domain-general Language Models by Playing Lottery Tickets
Yi Yang, Chen Zhang, Benyou Wang +1
Over-parameterized models, typically pretrained language models (LMs), have shown an appealing expressive power due to their small learning bias. However, the huge learning capacit…
Adaptable Text Matching via Meta-Weight Regulator
Bo Zhang, Chen Zhang, Fang Ma +1
Neural text matching models have been used in a range of applications such as question answering and natural language inference, and have yielded a good performance. However, these…