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20182026
most citedBioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining

1.2k citations · 1.4k across the 12 of their papers we have counts for

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8 papers · 1 filter

cs.LG2026

Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction

Jingyuan Li, Xiaoyi Jiang, Fukang Wen +5

Discrete diffusion models based on continuous-time Markov chains (CTMCs) have shown strong performance on language and discrete data generation, yet existing approaches typically p…

cs.LG2025

Trust Region Preference Approximation: A simple and stable reinforcement learning algorithm for LLM reasoning

Xuerui Su, Shufang Xie, Guoqing Liu +7

Recently, Large Language Models (LLMs) have rapidly evolved, approaching Artificial General Intelligence (AGI) while benefiting from large-scale reinforcement learning to enhance H…

cs.LG2025★ 2 cited

UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials

Gongbo Zhang, Yanting Li, Renqian Luo +31

Function in natural systems arises from one-dimensional sequences forming three-dimensional structures with specific properties. However, current generative models suffer from crit…

cs.LG2025★ 6 cited

HybriDNA: A Hybrid Transformer-Mamba2 Long-Range DNA Language Model

Mingqian Ma, Guoqing Liu, Chuan Cao +12

Advances in natural language processing and large language models have sparked growing interest in modeling DNA, often referred to as the "language of life". However, DNA modeling…

cs.LG2020

Accuracy Prediction with Non-neural Model for Neural Architecture Search

Renqian Luo, Xu Tan, Rui Wang +3

Neural architecture search (NAS) with an accuracy predictor that predicts the accuracy of candidate architectures has drawn increasing attention due to its simplicity and effective…

cs.LG2020

Semi-Supervised Neural Architecture Search

Renqian Luo, Xu Tan, Rui Wang +3

Neural architecture search (NAS) relies on a good controller to generate better architectures or predict the accuracy of given architectures. However, training the controller requi…