streaming
StreamingBench
StreamingBench: Assessing the Gap for MLLMs to Achieve Streaming Video Understanding
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StreamingBench evaluates Multimodal Large Language Models (MLLMs) in real-time, streaming video understanding tasks. 🌟
[NEW! 2025.05.15] 🔥: Seed1.5-VL achieved ALL model SOTA with a score of 82.80 on the Proactive Output.
[NEW! 2025.03.17] ⭐: ViSpeeker achieved Open-Source SOTA with a score of 61.60 on the… See the full description on the dataset page: https://huggingface.co/datasets/mjuicem/StreamingBench.Zhoulifeng-Streaming-Dataset
Zhoulifeng-Streaming-Dataset (峰哥直播语料 SFT 数据清洗流水线)
本项目旨在将“峰哥亡命天涯”的原始直播语音转录文本（ASR Transcripts）清洗、提纯、去重并重写，最终构建出高质量的大模型指令微调（SFT）和思维链（CoT）数据集。
本流水线包含 11 个核心处理步骤，通过规则过滤、统计学过滤、语义降噪以及大模型（LLM）深度重写等手段，将原始的五万多条粗糙问答，提纯为高逻辑密度、高“峰味”浓度的高质量训练集。
🗂️ 核心处理流程 (Data Pipeline)
数据清洗呈现严格的“漏斗状”递减，以下是完整的清洗流程序号与功能说明：
Step 01: 语音文本标点恢复 (Punctuation Generation)
脚本: 01_punctuation_generate.py
输入/输出: 生成 01_punc_transcripts/ 目录
说明: 针对原始 ASR 语音识别出的无断句纯文本，利用模型恢复正确的标点符号，为后续的语义切分和 QA… See the full description on the dataset page: https://huggingface.co/datasets/hzb29/Zhoulifeng-Streaming-Dataset.hls_streaming_mediaproof-pile-2-streaming
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Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen McAleer, Albert Q. Jiang, Jia Deng, Stella Biderman, Sean Welleck
The Proof-Pile-2 is a 55 billion token dataset of mathematical and scientific documents. This dataset was created in order to train the Llemma 7B and Llemma 34B models. It consists of three subsets:
arxiv (29B tokens): the ArXiv subset of RedPajama
open-web-math (15B tokens): The OpenWebMath… See the full description on the dataset page: https://huggingface.co/datasets/xavierdurawa/proof-pile-2-streaming.streaming_vlmstreamingbench