9 citations · 15 across the 11 of their papers we have counts for
12 papers
DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression
DeepSeek-AI, :, Anyi Xu +585
The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost of long-context computation…
OmniVAE: An Audio-Video VAE with Cross-Modal Alignment for Joint Generation
Jun Zhan, Chen Yang, Yitian Gong +23
Recent generative models are moving beyond silent video or standalone audio synthesis toward the joint generation of synchronized audio and video. Despite this progress, jointly ge…
DSpark: Confidence-Scheduled Speculative Decoding with Semi-Autoregressive Generation
Xin Cheng, Xingkai Yu, Chenze Shao +30
Speculative decoding accelerates Large Language Model (LLM) inference by decoupling draft generation from target verification. While recent parallel drafters efficiently propose lo…
Towards A Generative Protein Evolution Machine with DPLM-Evo
Xinyou Wang, Liang Hong, Jiasheng Ye +4
Proteins are shaped by gradual evolution under biophysical and functional constraints. Protein language models learn rich evolutionary constraints from large-scale sequences, and d…
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
DeepSeek-AI, Anyi Xu, Bangcai Lin +315
We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…
DetectiveQA: Evaluating Long-Context Reasoning on Detective Novels
Zhe Xu, Jiasheng Ye, Xiaoran Liu +8
Recently, significant efforts have been devoted to enhancing the long-context capabilities of Large Language Models (LLMs), particularly in long-context reasoning. To facilitate th…
Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance
Jiasheng Ye, Peiju Liu, Tianxiang Sun +3
Pretraining data of large language models composes multiple domains (e.g., web texts, academic papers, codes), whose mixture proportions crucially impact the competence of outcome…
LLM can Achieve Self-Regulation via Hyperparameter Aware Generation
Siyin Wang, Shimin Li, Tianxiang Sun +6
In the realm of Large Language Models (LLMs), users commonly employ diverse decoding strategies and adjust hyperparameters to control the generated text. However, a critical questi…
AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling
Jun Zhan, Junqi Dai, Jiasheng Ye +13
We introduce AnyGPT, an any-to-any multimodal language model that utilizes discrete representations for the unified processing of various modalities, including speech, text, images…
Diffusion Language Models Can Perform Many Tasks with Scaling and Instruction-Finetuning
Jiasheng Ye, Zaixiang Zheng, Yu Bao +2
The recent surge of generative AI has been fueled by the generative power of diffusion probabilistic models and the scalable capabilities of large language models. Despite their po…
DINOISER: Diffused Conditional Sequence Learning by Manipulating Noises
Jiasheng Ye, Zaixiang Zheng, Yu Bao +2
While diffusion models have achieved great success in generating continuous signals such as images and audio, it remains elusive for diffusion models in learning discrete sequence…
Energy-based Unknown Intent Detection with Data Manipulation
Yawen Ouyang, Jiasheng Ye, Yu Chen +3
Unknown intent detection aims to identify the out-of-distribution (OOD) utterance whose intent has never appeared in the training set. In this paper, we propose using energy scores…