LLMs
Datasets
All datasets matching “LLMs”uet_iai_nlp_data_for_llmsData sources come from the following categories:
1.Web crawler dataset:
Website UET (ĐH Công nghệ): tuyensinh.uet.vnu.edu.vn; new.uet.vnu.edu.vn
Website HUS (ĐH KHTN): hus.vnu.edu.vn
Website EUB (ĐH Kinh tế): ueb.vnu.edu.vn
Website IS (ĐH Quốc tế): is.vnu.edu.vn
Website Eduacation (ĐH Giáo dục): education.vnu.edu.vn
Website NXB ĐHQG: press.vnu.edu.vnList domain web crawler
CC100:link to CC100 vi
Vietnews: link to bk vietnews dataset
C4_vi: link to C4_vi
Folder Toxic store files demo… See the full description on the dataset page: https://huggingface.co/datasets/group2sealion/uet_iai_nlp_data_for_llms.llm-srbench
LLM-SRBench: Benchmark for Scientific Equation Discovery with LLMs
We introduce LLM-SRBench, a comprehensive benchmark with 239 challenging problems across four scientific domains specifically designed to evaluate LLM-based scientific equation discovery methods while preventing trivial memorization.
Our benchmark comprises two main categories: LSR-Transform, which transforms common physical models into less common mathematical representations to test reasoning beyond memorization… See the full description on the dataset page: https://huggingface.co/datasets/nnheui/llm-srbench.Videos-Dataset-For-LLMs-RAG-That-Require-Audio-Vidoes-And-Text
Dataset Overview
A collection of 27 domains (“topics”) and 3100 question-answer pair.
Each topic comes with average 117 QA pairs.Every QA entry comes with:
references: one or more source files the answer is extracted from
time with each reference comes the starting and ending time the answer is extracted from the reference
video_files: the video files where the answer can be found
(future) video title & description from metadata.csv
File structure
You-Are-Here!/… See the full description on the dataset page: https://huggingface.co/datasets/elmoghany/Videos-Dataset-For-LLMs-RAG-That-Require-Audio-Vidoes-And-Text.scaling-data-constrained-llms
Scaling Data-Constrained Language Models with Synthetic Data
This repository provides the pre-training corpora used in Scaling Data-Constrained Language Models with Synthetic Data (Findings of EACL 2026).
Overview
This repository contains multiple corpora designed to study data augmentation strategies for pre-training Japanese LLMs under a data-constrained data setting.
Starting from a limited Japanese Web corpus and a larger English Web corpus, we construct three… See the full description on the dataset page: https://huggingface.co/datasets/llm-jp/scaling-data-constrained-llms.llm_speedrun
LLM Speedrun token streams
Pre-tokenized training artifacts for the LLM speedrun exercises.
File
Description
Tokens
tokenizer_50M.bpe
JSON-serialized BPE tokenizer
—
fineweb-edu-10BT.shuffle.bin
Shuffled FineWeb-Edu sample/10BT token stream
9,440,023,113
smoltalk.shuffle.bin
Shuffled SmolTalk data/all token stream
875,269,408
The .bin files are headerless, little-endian unsigned 16-bit token IDs and can be memory-mapped with NumPy:
from huggingface_hub import… See the full description on the dataset page: https://huggingface.co/datasets/zkolter/llm_speedrun.Multi-turn_Long-context_Benchmark_for_LLMs
LoopServe: An Adaptive Dual-phase LLM Inference Acceleration System for Multi-Turn Dialogues
Arxiv: https://www.arxiv.org/abs/2507.13681
Huggingface: https://huggingface.co/papers/2507.13681
Introduction
LoopServe Multi-Turn Dialogue Benchmark is a comprehensive evaluation dataset comprising multiple diverse datasets designed to assess large language model performance in realistic conversational scenarios.
Unlike traditional benchmarks that place queries only at the end… See the full description on the dataset page: https://huggingface.co/datasets/TreeAILab/Multi-turn_Long-context_Benchmark_for_LLMs.