Datasets:
Data format
The paper benchmark contains 1,000 questions and 630 episodes. The benchmark and paper scoring records are published in separate Hugging Face repositories.
All JSONL files contain one JSON object per line.
Benchmark: psychemme/PsycheMME
| File | Contents |
|---|---|
benchmark/public/test.jsonl |
Question/episode IDs, relative media ID, category, task type, question, options, source group and supplied memory. |
benchmark/ground_truth.jsonl |
Matching public fields plus zero-based answer indices, answer texts, open reference, evidence and reference reasoning. |
benchmark/asr.jsonl |
Episode/media IDs, transcript segments, language and status. |
benchmark/media/video/ |
630 video files. |
metadata/media.jsonl |
Video mapping, file size, dimensions, frame rate, duration and source interval. |
metadata/episodes.jsonl |
Episode/source mapping and question count. |
metadata/sources.csv |
Original source links, identifiers and crop intervals. |
The download script prepares Ego4D from official originals and writes metadata/media.local.jsonl for the local media bindings used by evaluation.
media_id is relative to benchmark/media/. The model reads questions, ASR and media; references are supplied only to judging/scoring. Questions, reference answers and ASR retain the paper final-1000 content.
Paper records: psychemme/PsycheMME-logs
| File | Contents |
|---|---|
dataset/metadata_only.jsonl |
1,000 replay IDs, capability codes, task types and episode IDs. |
metadata/result_ids.jsonl |
Mapping from compact result IDs to original benchmark question and episode IDs. |
results/scoring_inputs.jsonl |
19,000 answer credits, rationale coverage, support/logic labels and status records. |
results/per_question_scores.jsonl |
Saved Raw/Verified scores. |
results/paper_table_2.json |
190 displayed main-table values. |
results/leaderboard.csv, results/per_capability_scores.csv |
Aggregate result tables. |
Use original_question_id and original_episode_id to join logs with the benchmark. replay --root points to the downloaded logs directory.
Validation
The validator checks public/reference ID closure, option indices, duplicates, capability codes and forbidden reference fields in public inputs. It rejects foreign or duplicate predictions. JSON Schemas are in schemas/; cross-record constraints are checked by Python.
Single-choice answers use a letter string. Multiple-select uses an exact set of letters with no partial-set credit. Open-answer credit is 0, 0.5 or 1 from a separately saved semantic judgment. Model output has nine keys: answer, G, W, N, T, S, A, R, M, with at least one informative rationale slot.
Memory context
memory_context is the public history supplied to the model. The loader passes this text unchanged to the prompt and to the reference-memory Judge context. It is present in 40 Memory questions; the paper's explicit-history ablation uses those 40 items.
memory_dependency describes annotated dependence on history for evaluation and is present in 54 Memory questions. Model-facing history is supplied through memory_context.
Both fields are optional and usually null. A null value means that no separate history or dependency annotation is attached to that question; video and ASR remain part of its input.
Evidence and time
Evidence can be a text annotation or a list of objects with times, offsets and source/display coordinates. ASR times are clip-relative; evidence may also record source-video coordinates. Use the coordinate and offset fields associated with each annotation.