47 citations · 48 across the 9 of their papers we have counts for
5 papers · 1 filter
Seed-Coder: Let the Code Model Curate Data for Itself
ByteDance Seed, Yuyu Zhang, Jing Su +24
Code data in large language model (LLM) pretraining is recognized crucial not only for code-related tasks but also for enhancing general intelligence of LLMs. Current open-source L…
Group Relative Knowledge Distillation: Learning from Teacher's Relational Inductive Bias
Chao Li, Changhua Zhou, Jia Chen
Knowledge distillation typically transfers knowledge from a teacher model to a student model by minimizing differences between their output distributions. However, existing distill…
Controllable Segmentation-Based Text-Guided Style Editing
Jingwen Li, Aravind Chandrasekar, Mariana Rocha +2
We present a novel approach for controllable, region-specific style editing driven by textual prompts. Building upon the state-space style alignment framework introduced by \emph{S…
Text-Driven Video Style Transfer with State-Space Models: Extending StyleMamba for Temporal Coherence
Chao Li, Minsu Park, Cristina Rossi +1
StyleMamba has recently demonstrated efficient text-driven image style transfer by leveraging state-space models (SSMs) and masked directional losses. In this paper, we extend the…
Yi-Lightning Technical Report
Alan Wake, Bei Chen, C. X. Lv +41
This technical report presents Yi-Lightning, our latest flagship large language model (LLM). It achieves exceptional performance, ranking 6th overall on Chatbot Arena, with particu…