datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Semantic-Flow-Dynamics-SFD
Semantic Flow Dynamics (SFD) — A Formally Specified Social-Science Theory Corpus
TL;DR: 614 Chinese-language formalized social-science concepts across 25
papers, UUID-linked with typed derivation relations (derives_from,
leads_to, falsified_by, …) — usable for knowledge-graph construction,
RAG over structured theory, or as a Chinese formal-reasoning corpus.
Author: 黃正宇 Cheng Yu HuangContact: mthree.tw@gmail.com
What This Dataset Is
This corpus is an ongoing… See the full description on the dataset page: https://huggingface.co/datasets/mthreetw/Semantic-Flow-Dynamics-SFD.stratasynth-belief-dynamics
StrataSynth Belief Dynamics
Part of the StrataSynth Synthetic Identity Engineering corpus.
2,114 turns · 100 conversations · 23 columns per turn
The most psychologically demanding dataset in the corpus. Grief, chronic illness, career crisis — scenarios where beliefs are under maximum and sustained pressure. The belief_resolution field drops measurably across pure_conflict arcs and recovers in reconnection arcs. Every trajectory is causal, not random.
Complexity level: 5 —… See the full description on the dataset page: https://huggingface.co/datasets/StrataSynth/stratasynth-belief-dynamics.dynamic_sonnet_llama3
Dynamic Sonnet - Llama3
Curated dataset for benchmarking LLM serving systems
In real-world service scenarios, each request comes with varying input token lengths.
Some requests generate only a few tokens, while others produce a significant number.
Traditional fixed-length benchmarks fail to capture this variability, making it difficult to accurately assess real-world throughput performance.
This dynamic nature of input token lengths is crucial as it directly affects key features of… See the full description on the dataset page: https://huggingface.co/datasets/squeezebits/dynamic_sonnet_llama3.dynamic_sonnet_llama2
Dynamic Sonnet - Llama2
Curated dataset for benchmarking LLM serving systems
In real-world service scenarios, each request comes with varying input token lengths.
Some requests generate only a few tokens, while others produce a significant number.
Traditional fixed-length benchmarks fail to capture this variability, making it difficult to accurately assess real-world throughput performance.
This dynamic nature of input token lengths is crucial as it directly affects key features of… See the full description on the dataset page: https://huggingface.co/datasets/squeezebits/dynamic_sonnet_llama2.dynamics-reasoning-traces-sample
DYNAMICS-8 Behavioural Reasoning Traces
Personality-conditioned chain-of-thought reasoning data for LLM alignment and persona fine-tuning.
What This Dataset Contains
Each record is a first-person behavioural response from a synthetic persona with a validated 8-dimension personality profile (DYNAMICS-8), accompanied by a structured reasoning trace showing which personality dimensions drove the decision.
This is not survey data. It is not statistical synthetic data. Each… See the full description on the dataset page: https://huggingface.co/datasets/Kronaxis/dynamics-reasoning-traces-sample.clinical_alignment_recovery_dynamics_v0.1Clinical Alignment Recovery Dynamics
Measures whether a model corrects earlier clinical errors when new signals appear.
Output JSON
recovered
recovery_type
correct_action
Runpython scorer.py --predictions predictions.jsonl --test_csv data/test.csv
alignment_recovery_dynamics_v01Clarus Alignment Recovery Dynamics v0.1
This dataset measures recovery after an alignment flip.
Focus
Not only whether a system flips
But whether it can recover
And whether it relapses under renewed pressure
Design
One row per step
Steps form a trajectory grouped by case_id
A recovery window defines how quickly recovery must occur
Columns
flip_signal_expected
none, early_warning, flip, cascade
first_flip_step_expected
First step where a flip is expected, or -1
recovery_expected
true if… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/alignment_recovery_dynamics_v01.dynamics-of-instruction-tuning
DoIT: Dynamics of Instruction Tuning
DoIT is a collection of over 40k human-curated instruction-output pairs in Chinese. I created from https://huggingface.co/datasets/ChiyuSONG/dynamics-of-instruction-tuning.
It collects all data in dynamics-of-instruction-tuning/curated/full/*.json.