complex-reasoning
imged_rl_grpo_no_reasoning_sft4_complex_edits_v2ft-llavaqwen1.5-1.8b-complex_reasoning-mergedft-lora-llavaqwen1.5-1.8b-complex_reasoningcomplex_arithmetic_vae-reasoning_Qwen2.5-3B-Instructft-moe-lora-llavaqwen1.5-1.8b-complex_reasoningllm-complex-reasoninggrpo_no_reasoning_sft4_complex_edits_v2_ckpt900_deepspeed
stem-reasoning-complex
STEM-Reasoning-Complex: High-Fidelity Scientific CoT Dataset
1. Dataset Summary
STEM-Reasoning-Complex is a curated collection of 118.255 high-quality samples designed for Supervised Fine-Tuning (SFT) and alignment of Large Language Models. The dataset focuses on four core disciplines: Biology, Mathematics, Physics, and Chemistry.
Unlike standard QA datasets, each entry provides a structured Chain-of-Thought (CoT) reasoning process, enabling models to learn… See the full description on the dataset page: https://huggingface.co/datasets/galaxyMindAiLabs/stem-reasoning-complex.A-Dataset-for-Complex-Reasoning-over-Textual-Knowledge-Graphs-in-Medicine
RiTeK: Medical Textual Knowledge Graph QA Benchmark
RiTeK is a benchmark for complex reasoning over medical Textual Knowledge Graphs (medical TKGs). It evaluates whether retrieval systems and Large Language Models (LLMs) can answer realistic medical questions by using both relational paths and textual entity descriptions.
Dataset Overview
The benchmark contains three medical graph QA subsets:
Dataset
Directory
Splits
KG file
ADint
Adint
train / dev / test… See the full description on the dataset page: https://huggingface.co/datasets/ChenAI2015/A-Dataset-for-Complex-Reasoning-over-Textual-Knowledge-Graphs-in-Medicine.stem-reasoning-complex
STEM-Reasoning-Complex: High-Fidelity Scientific CoT Dataset
1. Dataset Summary
STEM-Reasoning-Complex is a curated collection of 118.225 high-quality samples designed for Supervised Fine-Tuning (SFT) and alignment of Large Language Models. The dataset focuses on four core disciplines: Biology, Mathematics, Physics, and Chemistry.
Unlike standard QA datasets, each entry provides a structured Chain-of-Thought (CoT) reasoning process, enabling models to learn "internal… See the full description on the dataset page: https://huggingface.co/datasets/introvoyz041/stem-reasoning-complex.reasoning-sft-stem-reasoning-complex-FineProofs-126K
reasoning-sft-stem-reasoning-complex-FineProofs-126K
Combined converted dataset from two sources:
lm-provers/FineProofs-SFT (all config, 7.78k) — Mathematical Olympiad problems with chain-of-thought reasoning distilled from DeepSeek-Math-V2
galaxyMindAiLabs/stem-reasoning-complex (~118k) — STEM reasoning across Biology, Mathematics, Physics, Chemistry and Code
Format
Each row has three columns:
input — list of dicts [{"role": "user", "content": "..."}]
response —… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/reasoning-sft-stem-reasoning-complex-FineProofs-126K.atomic-formal-reasoning-complex
Atomic Formal Reasoning — Complex Numbers
Overview
This dataset contains high-quality Lean 4 formal proofs of complex number theorems, written in an explicit pedagogical calc-chain style. Each proof is fully verified, step-by-step, with no opaque tactics (simp, ring, omega are avoided). Every reasoning step is named and justified.
This is process supervision data — not just final answers. Each entry exposes the full reasoning chain, making it ideal for training models… See the full description on the dataset page: https://huggingface.co/datasets/7rouz/atomic-formal-reasoning-complex.llm-complex-reasoning-train-qwen2-72b-instruct-correct
Note
Data Seed from 基于封闭世界假设的复杂逻辑推理
Generate from Qwen2-72B-Instruct with prompt
train.jsonl for 推理答案和题目答案一致, no_train.jsonl推理答案和题目答案不一致
注: 题目答案不一定正确