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20152024
most citedUniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training

225 citations · 1.3k across the 62 of their papers we have counts for

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93 papers · 1 filter

cs.CL202437 cited

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Shuming Ma, Hongyu Wang, Lingxiao Ma +7

Recent research, such as BitNet, is paving the way for a new era of 1-bit Large Language Models (LLMs). In this work, we introduce a 1-bit LLM variant, namely BitNet b1.58, in whic…

cs.CL20233 cited

Calibrating LLM-Based Evaluator

Yuxuan Liu, Tianchi Yang, Shaohan Huang +6

Recent advancements in large language models (LLMs) on language modeling and emergent capabilities make them a promising reference-free evaluator of natural language generation qua…

cs.CL20233 cited

Large Language Model for Science: A Study on P vs. NP

Qingxiu Dong, Li Dong, Ke Xu +4

In this work, we use large language models (LLMs) to augment and accelerate research on the P versus NP problem, one of the most important open problems in theoretical computer sci…

cs.CL2023

KOSMOS-2.5: A Multimodal Literate Model

Tengchao Lv, Yupan Huang, Jingye Chen +13

The automatic reading of text-intensive images represents a significant advancement toward achieving Artificial General Intelligence (AGI). In this paper we present KOSMOS-2.5, a m…

cs.CL2023

PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training

Dawei Zhu, Nan Yang, Liang Wang +4

Large Language Models (LLMs) are trained with a pre-defined context length, restricting their use in scenarios requiring long inputs. Previous efforts for adapting LLMs to a longer…

cs.CL2023

Adapting Large Language Models to Domains via Reading Comprehension

Daixuan Cheng, Shaohan Huang, Furu Wei

We explore how continued pre-training on domain-specific corpora influences large language models, revealing that training on the raw corpora endows the model with domain knowledge…