6 citations · 7 across the 5 of their papers we have counts for
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cs.LG2025
Make It Long, Keep It Fast: End-to-End 10K Long User Behavior Sequence Modeling for Billion-Scale Douyin Recommendation
Lin Guan, Jia-Qi Yang, Zhishan Zhao +12
Short-video recommenders such as Douyin must exploit extremely long user behavior histories without breaking latency or cost budgets. We present an end-to-end industrial recommende…
cs.LG2025
SSPO: Self-traced Step-wise Preference Optimization for Process Supervision and Reasoning Compression
Yuyang Xu, Yi Cheng, Haochao Ying +5
Test-time scaling has proven effective in further enhancing the performance of pretrained Large Language Models (LLMs). However, mainstream post-training methods (i.e., reinforceme…
cs.CL2025★ 6 cited
Training an LLM-as-a-Judge Model: Pipeline, Insights, and Practical Lessons
Renjun Hu, Yi Cheng, Libin Meng +4
The rapid advancement of large language models (LLMs) has opened new possibilities for their adoption as evaluative judges. This paper introduces Themis, a fine-tuned LLM judge tha…