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20222026
most citedDeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

978 citations · 1k across the 16 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

cs.CL2023★ 1 cited

SCALE: Synergized Collaboration of Asymmetric Language Translation Engines

Xin Cheng, Xun Wang, Tao Ge +4

In this paper, we introduce SCALE, a collaborative framework that connects compact Specialized Translation Models (STMs) and general-purpose Large Language Models (LLMs) as one uni…

cs.LG2023

Partial-Label Regression

Xin Cheng, Deng-Bao Wang, Lei Feng +2

Partial-label learning is a popular weakly supervised learning setting that allows each training example to be annotated with a set of candidate labels. Previous studies on partial…

cs.CL2023

A Topic-aware Summarization Framework with Different Modal Side Information

Xiuying Chen, Mingzhe Li, Shen Gao +5

Automatic summarization plays an important role in the exponential document growth on the Web. On content websites such as CNN.com and WikiHow.com, there often exist various kinds…

cs.CL2023★ 17 cited

RWKV: Reinventing RNNs for the Transformer Era

Bo Peng, Eric Alcaide, Quentin Anthony +31

Transformers have revolutionized almost all natural language processing (NLP) tasks but suffer from memory and computational complexity that scales quadratically with sequence leng…

cs.CL2023

Decouple knowledge from parameters for plug-and-play language modeling

Xin Cheng, Yankai Lin, Xiuying Chen +2

Pre-trained language models(PLM) have made impressive results in various NLP tasks. It has been revealed that one of the key factors to their success is the parameters of these mod…

cs.CL2023★ 21 cited

Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory

Xin Cheng, Di Luo, Xiuying Chen +3

With direct access to human-written reference as memory, retrieval-augmented generation has achieved much progress in a wide range of text generation tasks. Since better memory wou…

cs.CL2023★ 2 cited

Towards Personalized Review Summarization by Modeling Historical Reviews from Customer and Product Separately

Xin Cheng, Shen Gao, Yuchi Zhang +5

Review summarization is a non-trivial task that aims to summarize the main idea of the product review in the E-commerce website. Different from the document summary which only need…