118 citations · 227 across the 13 of their papers we have counts for
14 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…
LLM-Powered Predictive Decision-Making for Sustainable Data Center Operations
Hanzhao Wang, Jingxuan Wu, Yumeng Li +2
The growing demand for AI-driven workloads, particularly from Large Language Models (LLMs), has raised concerns about the significant energy and resource consumption in data center…
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…
Adam's Law: Textual Frequency Law on Large Language Models
Hongyuan Adam Lu, Z. L., Victor Wei +5
While textual frequency has been validated as relevant to human cognition in reading speed, its relatedness to Large Language Models (LLMs) is seldom studied. We propose a novel re…
Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning
Haoran Luo, Haihong E, Guanting Chen +8
Retrieval-Augmented Generation (RAG) mitigates hallucination in LLMs by incorporating external knowledge, but relies on chunk-based retrieval that lacks structural semantics. Graph…
Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification
Shang Liu, Zhongze Cai, Guanting Chen +1
Predicting simple function classes has been widely used as a testbed for developing theory and understanding of the trained Transformer's in-context learning (ICL) ability. In this…
Understanding the Training and Generalization of Pretrained Transformer for Sequential Decision Making
Hanzhao Wang, Yu Pan, Fupeng Sun +4
In this paper, we consider the supervised pre-trained transformer for a class of sequential decision-making problems. The class of considered problems is a subset of the general fo…
Uncertainty Estimation and Quantification for LLMs: A Simple Supervised Approach
Linyu Liu, Yu Pan, Xiaocheng Li +1
In this paper, we study the problem of uncertainty estimation and calibration for LLMs. We begin by formulating the uncertainty estimation problem, a relevant yet underexplored are…
DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence
Daya Guo, Qihao Zhu, Dejian Yang +10
The rapid development of large language models has revolutionized code intelligence in software development. However, the predominance of closed-source models has restricted extens…
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
DeepSeek-AI, :, Xiao Bi +85
The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions,…
Facilitating Battery Swapping Services for Freight Trucks with Spatial-Temporal Demand Prediction
Linyu Liu, Zhen Dai, Shiji Song +2
Electrifying heavy-duty trucks offers a substantial opportunity to curtail carbon emissions, advancing toward a carbon-neutral future. However, the inherent challenges of limited b…
Learning to Make Adherence-Aware Advice
Guanting Chen, Xiaocheng Li, Chunlin Sun +1
As artificial intelligence (AI) systems play an increasingly prominent role in human decision-making, challenges surface in the realm of human-AI interactions. One challenge arises…
Fairer LP-based Online Allocation via Analytic Center
Guanting Chen, Xiaocheng Li, Yinyu Ye
In this paper, we consider an online resource allocation problem where a decision maker accepts or rejects incoming customer requests irrevocably in order to maximize expected rewa…
An Improved Analysis of LP-based Control for Revenue Management
Guanting Chen, Xiaocheng Li, Yinyu Ye
In this paper, we study a class of revenue management problems where the decision maker aims to maximize the total revenue subject to budget constraints on multiple type of resourc…