Datasets:

UniX-Lab
/

StreamOPD-Data

# Construction, prompts and temporal processing

## Annotation lineage

The source QA annotations come from ThinkStream's `streaming_rlvr_processed.jsonl`
and `streaming_cot_cold_processed_5_20.jsonl`. The construction pipeline selected
verifiable multiple-choice, binary and counting answers and converted them into
single-question chat records with source-video intervals.

The earlier base pool combined an 8,343-row pass-rate-selected subset and a
23,884-row verifiable subset, deduplicating on question text and ground truth to
produce 25,118 rows. The historical pass-rate selector used eight samples per
student/teacher and retained teacher score >= student score while excluding cases
where both were perfect. The published artifacts are the retained pool; complete
historical generation and sampling traces are not included.

`legacy_25118` stores that 25,118-row pool together with its explicit cue-instruction
teacher prompt. Ignoring the teacher fields yields the corresponding plain OPD QA
inputs. This configuration intentionally retains four previously confirmed
unreadable intervals and the eight known overlapping-source records.

`grpo_25114` removes those four unreadable intervals and retains the direct-answer
prompt suffixes actually used by the GRPO comparison. It does not contain cues and
does not apply the later eight-row source-overlap exclusion.

`current` additionally removes eight records tied to seven confirmed training/OVO
source-video overlaps. It stores the original student prompt, cue-positive teacher
prompt, raw reference, and matched-empty reference. `metadata/exclusions.json`
records the exact stable IDs and reasons, without internal filesystem information.

## Release transformations

The publication conversion:

1. Replaces internal absolute video paths with source-relative paths.
2. Renames the original numeric row index to `source_row_id` and adds a split-aware
   `sample_id`; the local conversion tool restores the trainer's row-index alias.
3. Gives all configurations one explicit Arrow schema and removes embedded pandas
   metadata. No binary video data is embedded.
4. Reconstructs convenience reference fields for historical configurations. It does
   not claim these references were used in historical training.
5. Replaces email text in two questions' answer choices with `[REDACTED_EMAIL]` in
   all corresponding prompts. The source IDs are 9390 and 20692; answer letters and
   ordering are unchanged. `privacy_redacted` marks those rows.

Except for these two documented contact-text replacements, original questions,
answers, cue text, prompt wrappers, video interval values and row order are preserved.
No credentials, machine addresses, private author names, internal logs or source
absolute paths are intentionally distributed.

## Video intervals and frames

`video_start` and `video_end` are seconds relative to the referenced video file.
The conversion uses a maximum preceding window of 30 seconds:

```text
start = max(0, query_timestamp - 30)
end   = query_timestamp
```

A timestamp audit matched all 25,106 current rows to source query timestamps and
found their `video_end` equal to the query time. 445 training rows have nonzero start
times. Stored intervals are authoritative for reconstruction; do not replace them
with whole-video sampling.

The verified training input preflight used decord on CPU, one decoder thread, and
qwen-vl-utils 0.0.14 frame-range and frame-count helpers. Frame indices were generated
by uniformly spacing between the decoder-resolved start and end indices and rounding
to integer frame indices. The four unreadable intervals failed this input check.

The release does not bake a universal FPS, number of frames or pixel budget into
the dataset. Actual frame counts and resizing depend on the model processor and
resolved training configuration. Keep those settings with experiment records.
Qwen3.5 and Qwen3-VL use different processors and model modes. For CueGate, the
teacher positive/reference scoring branches reuse the student's decoded visual
payload while changing the text prompt.

Four recent frames at deployment are a separate evaluation protocol. Do not
reinterpret every training example as exactly four frames. Frame-index sampling
alone is not a certification of strict absolute presentation-timestamp causality.

## Visual cues and reference prompts

Existing cues were generated with Qwen3.5-27B, using instructions to point to a time
or visual region rather than answer the question. Generation stripped recognized
answer-option blocks and used automated leakage checks/retries. The historical
stripping did not cover every option layout, and automated acceptance does not
prove cue correctness or absence of answer information.

The cue generator passed a source-video URL without applying the student's stored
start/end interval. Consequently it could inspect the full source clip, including
post-query content. These existing annotations must not be described as prefix-only.
A later prefix/full pilot is outside this release; its outputs are not mixed in.

For a row with a cue:

- Student and raw reference: original question and options.
- Teacher positive: original question plus the cue instruction wrapper and actual cue.
- Empty reference: same wrapper, with the cue content empty.

For a fallback row, all three teacher message fields equal the original student
prompt, `cue_available` is false, and `cue_text` is null. Validation has no cues.

## Known data limitations

An existing audit identified 252 current MCQs without an explicit option block.
The stable IDs are retained in `metadata/known_issues.json`; this publication does
not invent missing choices or claim to resolve the answer mapping. Known source
overlap exclusion is incomplete across benchmarks, and no exhaustive human cue
leakage filter has been applied. Training/validation video IDs should be inspected
for any additional split-specific use case.

	# Construction, prompts and temporal processing

	## Annotation lineage

	The source QA annotations come from ThinkStream's `streaming_rlvr_processed.jsonl`
	and `streaming_cot_cold_processed_5_20.jsonl`. The construction pipeline selected
	verifiable multiple-choice, binary and counting answers and converted them into
	single-question chat records with source-video intervals.

	The earlier base pool combined an 8,343-row pass-rate-selected subset and a
	23,884-row verifiable subset, deduplicating on question text and ground truth to
	produce 25,118 rows. The historical pass-rate selector used eight samples per
	student/teacher and retained teacher score >= student score while excluding cases
	where both were perfect. The published artifacts are the retained pool; complete
	historical generation and sampling traces are not included.

	`legacy_25118` stores that 25,118-row pool together with its explicit cue-instruction
	teacher prompt. Ignoring the teacher fields yields the corresponding plain OPD QA
	inputs. This configuration intentionally retains four previously confirmed
	unreadable intervals and the eight known overlapping-source records.

	`grpo_25114` removes those four unreadable intervals and retains the direct-answer
	prompt suffixes actually used by the GRPO comparison. It does not contain cues and
	does not apply the later eight-row source-overlap exclusion.

	`current` additionally removes eight records tied to seven confirmed training/OVO
	source-video overlaps. It stores the original student prompt, cue-positive teacher
	prompt, raw reference, and matched-empty reference. `metadata/exclusions.json`
	records the exact stable IDs and reasons, without internal filesystem information.

	## Release transformations

	The publication conversion:

	1. Replaces internal absolute video paths with source-relative paths.
	2. Renames the original numeric row index to `source_row_id` and adds a split-aware
	`sample_id`; the local conversion tool restores the trainer's row-index alias.
	3. Gives all configurations one explicit Arrow schema and removes embedded pandas
	metadata. No binary video data is embedded.
	4. Reconstructs convenience reference fields for historical configurations. It does
	not claim these references were used in historical training.
	5. Replaces email text in two questions' answer choices with `[REDACTED_EMAIL]` in
	all corresponding prompts. The source IDs are 9390 and 20692; answer letters and
	ordering are unchanged. `privacy_redacted` marks those rows.

	Except for these two documented contact-text replacements, original questions,
	answers, cue text, prompt wrappers, video interval values and row order are preserved.
	No credentials, machine addresses, private author names, internal logs or source
	absolute paths are intentionally distributed.

	## Video intervals and frames

	`video_start` and `video_end` are seconds relative to the referenced video file.
	The conversion uses a maximum preceding window of 30 seconds:

	```text
	start = max(0, query_timestamp - 30)
	end = query_timestamp
	```

	A timestamp audit matched all 25,106 current rows to source query timestamps and
	found their `video_end` equal to the query time. 445 training rows have nonzero start
	times. Stored intervals are authoritative for reconstruction; do not replace them
	with whole-video sampling.

	The verified training input preflight used decord on CPU, one decoder thread, and
	qwen-vl-utils 0.0.14 frame-range and frame-count helpers. Frame indices were generated
	by uniformly spacing between the decoder-resolved start and end indices and rounding
	to integer frame indices. The four unreadable intervals failed this input check.

	The release does not bake a universal FPS, number of frames or pixel budget into
	the dataset. Actual frame counts and resizing depend on the model processor and
	resolved training configuration. Keep those settings with experiment records.
	Qwen3.5 and Qwen3-VL use different processors and model modes. For CueGate, the
	teacher positive/reference scoring branches reuse the student's decoded visual
	payload while changing the text prompt.

	Four recent frames at deployment are a separate evaluation protocol. Do not
	reinterpret every training example as exactly four frames. Frame-index sampling
	alone is not a certification of strict absolute presentation-timestamp causality.

	## Visual cues and reference prompts

	Existing cues were generated with Qwen3.5-27B, using instructions to point to a time
	or visual region rather than answer the question. Generation stripped recognized
	answer-option blocks and used automated leakage checks/retries. The historical
	stripping did not cover every option layout, and automated acceptance does not
	prove cue correctness or absence of answer information.

	The cue generator passed a source-video URL without applying the student's stored
	start/end interval. Consequently it could inspect the full source clip, including
	post-query content. These existing annotations must not be described as prefix-only.
	A later prefix/full pilot is outside this release; its outputs are not mixed in.

	For a row with a cue:

	- Student and raw reference: original question and options.
	- Teacher positive: original question plus the cue instruction wrapper and actual cue.
	- Empty reference: same wrapper, with the cue content empty.

	For a fallback row, all three teacher message fields equal the original student
	prompt, `cue_available` is false, and `cue_text` is null. Validation has no cues.

	## Known data limitations

	An existing audit identified 252 current MCQs without an explicit option block.
	The stable IDs are retained in `metadata/known_issues.json`; this publication does
	not invent missing choices or claim to resolve the answer mapping. Known source
	overlap exclusion is incomplete across benchmarks, and no exhaustive human cue
	leakage filter has been applied. Training/validation video IDs should be inspected
	for any additional split-specific use case.