activity
20242026
most citedDeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

978 citations · 1.6k across the 14 of their papers we have counts for

collaborators

15 papers

cs.CL2026

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…

cs.CL2025★ 8 cited

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…

astro-ph.IM2025★ 1 cited

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

Jinghang Shi, Xiaoyu Tang, Yang Huang +4

Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…

cs.CL2025

The Bias is in the Details: An Assessment of Cognitive Bias in LLMs

R. Alexander Knipper, Charles S. Knipper, Kaiqi Zhang +3

As Large Language Models (LLMs) are increasingly embedded in real-world decision-making processes, it becomes crucial to examine the extent to which they exhibit cognitive biases.…

cs.LG2025★ 1 cited

Assay2Mol: large language model-based drug design using BioAssay context

Yifan Deng, Spencer S. Ericksen, Anthony Gitter

Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…

cs.CL2025★ 5 cited

FinanceReasoning: Benchmarking Financial Numerical Reasoning More Credible, Comprehensive and Challenging

Zichen Tang, Haihong E, Ziyan Ma +10

We introduce FinanceReasoning, a novel benchmark designed to evaluate the reasoning capabilities of large reasoning models (LRMs) in financial numerical reasoning problems. Compare…

cs.CL2025

Jailbreak Distillation: Renewable Safety Benchmarking

Jingyu Zhang, Ahmed Elgohary, Xiawei Wang +5

Large language models (LLMs) are rapidly deployed in critical applications, raising urgent needs for robust safety benchmarking. We propose Jailbreak Distillation (JBDistill), a no…

cs.LG2025

RouteNator: A Router-Based Multi-Modal Architecture for Generating Synthetic Training Data for Function Calling LLMs

Vibha Belavadi, Tushar Vatsa, Dewang Sultania +5

This paper addresses fine-tuning Large Language Models (LLMs) for function calling tasks when real user interaction data is unavailable. In digital content creation tools, where us…

cs.CL2025★ 978 cited

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

DeepSeek-AI, Daya Guo, Dejian Yang +195

General reasoning represents a long-standing and formidable challenge in artificial intelligence. Recent breakthroughs, exemplified by large language models (LLMs) and chain-of-tho…

cs.CL2024★ 268 cited

DeepSeek-V3 Technical Report

DeepSeek-AI, Aixin Liu, Bei Feng +195

We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token. To achieve efficient inference and cost-effec…

cs.DC2024

Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning

Wei An, Xiao Bi, Guanting Chen +49

The rapid progress in Deep Learning (DL) and Large Language Models (LLMs) has exponentially increased demands of computational power and bandwidth. This, combined with the high cos…

cs.SE2024★ 49 cited

DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

DeepSeek-AI, Qihao Zhu, Daya Guo +37

We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks. Specifically, D…

cs.AI2024★ 47 cited

DeepSeek-VL: Towards Real-World Vision-Language Understanding

Haoyu Lu, Wen Liu, Bo Zhang +12

We present DeepSeek-VL, an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications. Our approach is structured around three ke…

cs.SE2024★ 118 cited

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…

cs.CL2024★ 95 cited

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,…