most citedDeepSeek-V3 Technical Report

268 citations · 276 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL20258 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…

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

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.CV2025

CGEarthEye:A High-Resolution Remote Sensing Vision Foundation Model Based on the Jilin-1 Satellite Constellation

Zhiwei Yi, Xin Cheng, Jingyu Ma +5

Deep learning methods have significantly advanced the development of intelligent rinterpretation in remote sensing (RS), with foundational model research based on large-scale pre-t…

cs.CL2025

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…