2 citations · 3 across the 7 of their papers we have counts for
8 papers
RollVerify: Bridging Efficiency and Accuracy in Long-Tail Rollout Reinforcement Learning
Yongqiang Yao, Jinru Tan, Kaihuan Liang +5
Reinforcement learning is crucial for improving large language models' reasoning and generalization. It relies on massive rollouts whose lengths become increasingly long-tailed as…
SenseNova-U1.5: Towards Native Unified Visual Intelligence
Haiwen Diao, Jiahao Wang, Chenjing Ding +62
We launch SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free and VAE-free architecture.…
Incremental BPE Tokenization
Shenghu Jiang, Ruihao Gong
We propose a novel algorithm for incremental Byte Pair Encoding (BPE) tokenization. The algorithm processes each input byte in worst-case time, leading to a…
SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture
Haiwen Diao, Penghao Wu, Hanming Deng +55
Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fra…
TokenSim: Enabling Hardware and Software Exploration for Large Language Model Inference Systems
Feiyang Wu, Zhuohang Bian, Guoyang Duan +6
The increasing demand for large language model (LLM) serving has necessitated significant advancements in the optimization and profiling of LLM inference systems. As these models b…
Hierarchical Balance Packing: Towards Efficient Supervised Fine-tuning for Long-Context LLM
Yongqiang Yao, Jingru Tan, Kaihuan Liang +7
Training Long-Context Large Language Models (LLMs) is challenging, as hybrid training with long-context and short-context data often leads to workload imbalances. Existing works ma…
OmniBal: Towards Fast Instruction-Tuning for Vision-Language Models via Omniverse Computation Balance
Yongqiang Yao, Jingru Tan, Feizhao Zhang +8
Vision-language instruction-tuning models have recently achieved significant performance improvements. In this work, we discover that large-scale 3D parallel training on those mode…
2023 Low-Power Computer Vision Challenge (LPCVC) Summary
Leo Chen, Benjamin Boardley, Ping Hu +27
This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC). Since 2015, LPCVC has been an international competition devoted to tackling the challenge of compu…