1 code implementation • 17 Feb 2024 • Shaokun Zhang, Jieyu Zhang, Jiale Liu, Linxin Song, Chi Wang, Ranjay Krishna, Qingyun Wu
Researchers and practitioners have recently reframed powerful Large Language Models (LLMs) as agents, enabling them to automate complex tasks largely via the use of specialized functions.
1 code implementation • 18 Jan 2024 • Linxin Song, Yan Cui, Ao Luo, Freddy Lecue, Irene Li
Transformer-based models excel in various natural language processing (NLP) tasks, attracting countless efforts to explain their inner workings.
1 code implementation • 27 Sep 2023 • Linxin Song, Jieyu Zhang, Lechao Cheng, Pengyuan Zhou, Tianyi Zhou, Irene Li
Recent developments in large language models (LLMs) have shown promise in enhancing the capabilities of natural language processing (NLP).
no code implementations • 24 Aug 2023 • Ao Luo, Linxin Song, Keisuke Nonaka, Kyohei Unno, Heming Sun, Masayuki Goto, Jiro Katto
In recent years, the task of learned point cloud compression has gained prominence.
no code implementations • 19 Jun 2023 • Linxin Song, Jieyu Zhang, Xiaotian Lu, Tianyi Zhou
Instead of tuning the coefficient for each query round, which is sensitive and time-consuming, we propose the curriculum Firth bias reduction (CHAIN) that can automatically adjust the coefficient to be adaptive to the training process.
2 code implementations • 6 Oct 2022 • Jieyu Zhang, Linxin Song, Alexander Ratner
In particular, it is built on a mixture of Bayesian label models, each corresponding to a global pattern of correlation, and the coefficients of the mixture components are predicted by a Gaussian Process classifier based on instance features.
2 code implementations • 6 Oct 2022 • Linxin Song, Jieyu Zhang, Tianxiang Yang, Masayuki Goto
To obtain a large amount of training labels inexpensively, researchers have recently adopted the weak supervision (WS) paradigm, which leverages labeling rules to synthesize training labels rather than using individual annotations to achieve competitive results for natural language processing (NLP) tasks.