9 citations · 10 across the 7 of their papers we have counts for
8 papers
Put Teacher in Student's Shoes: Cross-Distillation for Ultra-compact Model Compression Framework
Maolin Wang, Jun Chu, Sicong Xie +4
In the era of mobile computing, deploying efficient Natural Language Processing (NLP) models in resource-restricted edge settings presents significant challenges, particularly in e…
CSR:Achieving 1 Bit Key-Value Cache via Sparse Representation
Hongxuan Zhang, Yao Zhao, Jiaqi Zheng +3
The emergence of long-context text applications utilizing large language models (LLMs) has presented significant scalability challenges, particularly in memory footprint. The linea…
Mitigate Position Bias with Coupled Ranking Bias on CTR Prediction
Yao Zhao, Zhining Liu, Tianchi Cai +3
Position bias, i.e., users' preference of an item is affected by its placing position, is well studied in the recommender system literature. However, most existing methods ignore t…
DNS-Rec: Data-aware Neural Architecture Search for Recommender Systems
Sheng Zhang, Maolin Wang, Yao Zhao +6
In the era of data proliferation, efficiently sifting through vast information to extract meaningful insights has become increasingly crucial. This paper addresses the computationa…
Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation Accuracy
Yao Zhao, Zhitian Xie, Chen Liang +2
As Large Language Models (LLMs) have made significant advancements across various tasks, such as question answering, translation, text summarization, and dialogue systems, the need…
Large Multimodal Model Compression via Efficient Pruning and Distillation at AntGroup
Maolin Wang, Yao Zhao, Jiajia Liu +5
The deployment of Large Multimodal Models (LMMs) within AntGroup has significantly advanced multimodal tasks in payment, security, and advertising, notably enhancing advertisement…
On the Opportunities of Green Computing: A Survey
You Zhou, Xiujing Lin, Xiang Zhang +38
Artificial Intelligence (AI) has achieved significant advancements in technology and research with the development over several decades, and is widely used in many areas including…
Fast Chain-of-Thought: A Glance of Future from Parallel Decoding Leads to Answers Faster
Hongxuan Zhang, Zhining Liu, Yao Zhao +4
In this work, we propose FastCoT, a model-agnostic framework based on parallel decoding without any further training of an auxiliary model or modification to the LLM itself. FastCo…