JonesLin/video-vqa-sft-mixed

Video VQA SFT — mixed reasoning and direct answers

Supervised fine-tuning data for video question answering. Each sample appears in up to two styles: one that reasons before answering, and one that answers directly. Which style the model should produce is signalled in the user turn, not in a system prompt, because that is what the evaluation harnesses send.

Contents

Records	356,033
Distinct videos	19,808
Reasoning style	211,238
Direct style	144,795

Source dataset	Records
TimeLens-100K	320,094
TimeLens-100K hallucination suppression	27,100
THUMOS-14	8,839

TimeLens records by video source: cosmo_cap 143,862, internvid_vtime 75,478, didemo 56,628, queryd 27,701, hirest 16,425.

Question types among TimeLens and THUMOS-14 reasoning records: yes_no_count 68,849, direct_action 64,425, multiple_choice 64,415.

Record format

{
  "sample_id": "thumos14:validation/video_validation_0000683.mp4:baseball pitch:0",
  "answer_style": "reasoning",
  "system": "You are a helpful assistant.",
  "dataset_source": "thumos14",
  "video_path": "validation/video_validation_0000683.mp4",
  "question_type": "yes_no_count",
  "subagent_id": "d694b721-86a4-4bfe-b7ec-c4974fb2e444",
  "conversations": [
    {"from": "human", "value": "Video: ...\nQuestion: ...\nPlease think the following query step by step and provide your final concise response as 'FINAL ANSWER: <answer>'."},
    {"from": "gpt", "value": "...reasoning...\n\nFINAL ANSWER: 1"}
  ],
  "reference_answer": "1"
}

video_path is relative to the source dataset's own video archive; videos are not included here. Records sharing a subagent_id were produced by one generation call.

The two styles

The instruction that selects a style lives in the user turn:

• reasoning — ends with Please think the following query step by step and provide your final concise response as 'FINAL ANSWER: <answer>'. The target is a short chain of observations followed by FINAL ANSWER: <answer>.
• direct — ends with Do not include any additional text or explanation in your response. The target is the bare answer: a count, Yes/No, or a single option letter. The hallucination-suppression subset keeps its upstream prompts, which say You can only answer yes or no or Do not explain. instead.

The signals are mutually exclusive across the whole file, verified: 211,238/211,238 reasoning records carry the reasoning instruction and 0 carry a direct one; 144,795/144,795 direct records carry a direct instruction and 0 carry the reasoning one. 211,238/211,238 reasoning targets contain FINAL ANSWER:; 144,795/144,795 direct targets are a single line; 65,437/65,437 multiple-choice direct targets are one letter.

system is "You are a helpful assistant." on every record, matching the default in OVO-Bench and StreamingBench evaluation. No task instruction is placed there, since the benchmarks do not send one.

How it was built

Answers were generated with gemini-3.8-flash, gemini-3.7-flash and gemini-3.6-flash at low thinking level, sending one video with one event's three questions per request. Both styles come from a single generation: the model returns a reasoning field and an answer field, which become the two records. The hallucination-suppression subset is the exception; see below. Direct answers are normalised to a bare value; samples where the model hedged (e.g. "1 (or 4 including replays)") keep only the reasoning record.

Hallucination-suppression subset

13,551 questions come from TimeLens-100K's hallucination-suppression probe sets. Each shows one video and asks something that video cannot support: whether its latest frames answer a question taken from another video (OVO), whether it is time to emit another video's trigger phrase (streaming readiness), or a multiple-choice question whose correct option is "Unable to answer" (cross-video positive). The cross-video negatives are the paired control: an answerable question about the same video's own content.

Subset	Questions	Reasoning records
OVO evidence sufficiency	6,431	6,430
Streaming readiness	5,991	5,991
Cross-video MC, positive	1,000	999
Cross-video MC, answerable control	129	129

These targets were not taken from the model. The labels are constructed rather than annotated, and the upstream generator validates them (0 violations on every invariant its report checks), so the reference is the target. Generation told the model the correct answer and asked it to ground that answer in what the video shows or lacks. A reasoning record is kept only when the model's own stated answer agrees with the reference; otherwise the question has a direct record only. Direct prompts are the subset's upstream prompts, verbatim. Each request carried up to six of one video's questions.

Video coverage is uneven across the run

TimeLens has 15 questions per video: 5 events, each asked three ways. Questions per video actually taken from the canonical question set, counting reasoning records:

Questions taken	Videos
3	3
6	865
9	14,924
10	1
11	2
12	187
13	3
14	4
15	3,425

19,414 of TimeLens-100K's 19,414 videos are represented. The largest group is 14,924 videos at 9 questions. Videos at 15 come from the earliest batches, which had no per-video cap; the cap was added later but did not bind until a bug was fixed, because it was applied to the unprocessed questions rather than to all of a video's questions. Later runs took whole events per video, three questions at a time, so the deeper groups are later events of videos already covered, not repeats of the same event. Treat the 15-question videos as a distinct, denser subset if per-video balance matters for your training mix.

Known limitations

• Reasoning is short. A median of 133 characters (p90 214). Most records are a single grounded observation rather than a multi-step chain. This follows from the low thinking level and from batching several questions per request.
• THUMOS-14 label noise. Reference answers were derived faithfully from THUMOS-14 temporal annotations, but those annotations have errors: on video_validation_0000266 several spans containing clear baseball pitches are labelled FrisbeeCatch or Ambiguous. reference_answer is kept as metadata and did not drive generation.
• Not verified against ground truth. Outside the hallucination-suppression subset, these are model outputs, not human labels. Agreement with THUMOS-14 references is 50.2%; with TimeLens multiple-choice references, 95.6%.
• Hallucination labels are almost all "No". 12,422 of the 13,551 hallucination-suppression direct targets are "No"; the cross-video negatives are the only answerable control. Mixing the whole subset in tilts yes/no readiness questions toward "No", so weigh it in your training mix.
• OVO-Bench overlap excluded. The 105 THUMOS-14 test questions whose videos appear in OVO-Bench's REC split are excluded, since OVO-Bench uses a byte-identical prompt template and is an evaluation target.
• Contains transcribed on-screen text. A handful of records repeat business contact details that appear in the source videos, including seven email addresses.