datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Feedback_Friction_Dataset
Feedback Friction Dataset
This dataset contains the LLaMA-4 Maverick results from the iterative feedback experiments described in the paper: FEEDBACK FRICTION: LLMs Struggle to Fully Incorporate External Feedback.
Github Repository: https://github.com/JHU-CLSP/Feedback-Friction
Note: While the paper evaluated multiple frontier models including LLaMA-3.3-70B-Instruct, LLaMA-4-Scout-17B-16E-Instruct, Claude 3.7 Sonnet, and Claude 3.7 Sonnet with Extended Thinking, this dataset… See the full description on the dataset page: https://huggingface.co/datasets/Dongwei/Feedback_Friction_Dataset.single-turn-eval-meta_feedback_qwen3-4b_step2_gpt-5.4_gepa-n32
Single-turn eval — violetxi/meta_feedback_qwen3-4b_step2_gpt-5.4_gepa
Generated by teaching/inference/single_turn_eval_vllm.py. One row per problem; samples is the list of model responses, scores is per-sample correctness, and mean/best/worst are the aggregates used by mean@N / best@N / worst@N.
Eval results (n_samples_per_example = 32)
Overall
metric
value
n_examples
1006
mean@32
0.1796
best@32
0.3588
worst@32
0.0477
pass_rate
0.3588… See the full description on the dataset page: https://huggingface.co/datasets/violetxi/single-turn-eval-meta_feedback_qwen3-4b_step2_gpt-5.4_gepa-n32.single-turn-eval-meta_feedback_qwen3-4b_step2_gpt-5-nano_gepa-n32
Single-turn eval — violetxi/meta_feedback_qwen3-4b_step2_gpt-5-nano_gepa
Generated by teaching/inference/single_turn_eval_vllm.py. One row per problem; samples is the list of model responses, scores is per-sample correctness, and mean/best/worst are the aggregates used by mean@N / best@N / worst@N.
Eval results (n_samples_per_example = 32)
Overall
metric
value
n_examples
1006
mean@32
0.1804
best@32
0.3569
worst@32
0.0398
pass_rate… See the full description on the dataset page: https://huggingface.co/datasets/violetxi/single-turn-eval-meta_feedback_qwen3-4b_step2_gpt-5-nano_gepa-n32.