22 citations · 55 across the 14 of their papers we have counts for
14 papers
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…
DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
DeepSeek-AI, Aixin Liu, Aoxue Mei +260
We introduce DeepSeek-V3.2, a model that harmonizes high computational efficiency with superior reasoning and agent performance. The key technical breakthroughs of DeepSeek-V3.2 ar…
PHM-Bench: A Domain-Specific Benchmarking Framework for Systematic Evaluation of Large Models in Prognostics and Health Management
Puyu Yang, Laifa Tao, Zijian Huang +11
With the rapid advancement of generative artificial intelligence, large language models (LLMs) are increasingly adopted in industrial domains, offering new opportunities for Progno…
Towards Efficient Exact Optimization of Language Model Alignment
Haozhe Ji, Cheng Lu, Yilin Niu +5
The alignment of language models with human preferences is vital for their application in real-world tasks. The problem is formulated as optimizing the model's policy to maximize t…
Language Model Decoding as Direct Metrics Optimization
Haozhe Ji, Pei Ke, Hongning Wang +1
Despite the remarkable advances in language modeling, current mainstream decoding methods still struggle to generate texts that align with human texts across different aspects. In…
Tailoring Language Generation Models under Total Variation Distance
Haozhe Ji, Pei Ke, Zhipeng Hu +2
The standard paradigm of neural language generation adopts maximum likelihood estimation (MLE) as the optimizing method. From a distributional view, MLE in fact minimizes the Kullb…
Curriculum-Based Self-Training Makes Better Few-Shot Learners for Data-to-Text Generation
Pei Ke, Haozhe Ji, Zhenyu Yang +4
Despite the success of text-to-text pre-trained models in various natural language generation (NLG) tasks, the generation performance is largely restricted by the number of labeled…
LaMemo: Language Modeling with Look-Ahead Memory
Haozhe Ji, Rongsheng Zhang, Zhenyu Yang +2
Although Transformers with fully connected self-attentions are powerful to model long-term dependencies, they are struggling to scale to long texts with thousands of words in langu…
DiscoDVT: Generating Long Text with Discourse-Aware Discrete Variational Transformer
Haozhe Ji, Minlie Huang
Despite the recent advances in applying pre-trained language models to generate high-quality texts, generating long passages that maintain long-range coherence is yet challenging f…
JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
Pei Ke, Haozhe Ji, Yu Ran +5
Existing pre-trained models for knowledge-graph-to-text (KG-to-text) generation simply fine-tune text-to-text pre-trained models such as BART or T5 on KG-to-text datasets, which la…
CPM: A Large-scale Generative Chinese Pre-trained Language Model
Zhengyan Zhang, Xu Han, Hao Zhou +22
Pre-trained Language Models (PLMs) have proven to be beneficial for various downstream NLP tasks. Recently, GPT-3, with 175 billion parameters and 570GB training data, drew a lot o…
Generating Commonsense Explanation by Extracting Bridge Concepts from Reasoning Paths
Haozhe Ji, Pei Ke, Shaohan Huang +2
Commonsense explanation generation aims to empower the machine's sense-making capability by generating plausible explanations to statements against commonsense. While this task is…
Language Generation with Multi-Hop Reasoning on Commonsense Knowledge Graph
Haozhe Ji, Pei Ke, Shaohan Huang +3
Despite the success of generative pre-trained language models on a series of text generation tasks, they still suffer in cases where reasoning over underlying commonsense knowledge…
SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge
Pei Ke, Haozhe Ji, Siyang Liu +2
Most of the existing pre-trained language representation models neglect to consider the linguistic knowledge of texts, which can promote language understanding in NLP tasks. To ben…