MV-Omni

Instruction-diversity augment (v6) release of the MixtureVitae-Omni (MV-Omni) training text -- 6 shards. Adds 2 new columns (id, task) on top of the v5 release's text/metadata, and increases row count via a new reverse task (see item 4 below); modality-token payloads for every PRE-EXISTING turn are byte-identical to v5, only instruction phrasing and framing text changed.

What changed and why (v6, 2026-08-04)

Code-only, no LLM generation -- deterministic sha256(id) % N pool selection, same mechanism as EmpathicRobotics/harmony4d-flattened (v2) and EmpathicRobotics/synth-llava (v4/v5). Verified directly on real data first (5,000-record scan): all 4 of MV-Omni's fixed lead sentences were 100% byte-identical across every occurrence -- exactly the "cheap to construct... lacking diversity" pattern the LLaVA paper (arXiv 2304.08485) calls out, and Huu's MV1-instruct directive (vary instruction phrasing, don't mechanically drop raw fields into USER:/ASSISTANT:) asks to fix.

1. Instruction-phrasing pool for the 4 previously-fixed lead sentences -- "Listen to this and tell me what you heard.", "Now repeat what you heard.", "Describe the image.", "What would the speaker narrating this scene say?" -- each replaced with 1 of 5 hand-written phrasings (deterministic per turn). The "What did you hear/say at time N?" family (timestamped listening-comprehension turns) gets the same treatment via a template pool that substitutes only the verb/timestamp, not the frame.
2. Context lead-in for video_metadata_timestamped records. The folded YouTube-metadata preamble (see v4's fix) was glued directly onto the first real question with zero framing. A short lead-in phrase pool ("Video context:", "Background on this clip:", ...) is now prepended to the first turn only.
3. New id and task columns. MV-Omni's raw data never had a row id; one is assigned deterministically (mv_omni_{shard}_{line}). task labels each row's dominant turn family -- listen_transcribe / video_metadata_timestamped / image_describe / image_seed2_reverse / other -- computed from the same turn-parsing logic used for the augment itself (not a separate heuristic), so the format families this dataset mixes are now queryable directly instead of only inferrable via regex.
4. Reverse task: caption -> seed2 (new rows, generation-direction fix). MV-Omni is almost entirely media->text (audio->transcript, image->caption) -- the training mix's single largest source teaches understanding, not generation. For every turn where the USER side embeds real <seed2_N> tokens (the "now you're looking at the image, what do you see" turn), one new row is added with the sides swapped: USER = a draw/imagine instruction + the row's own real caption text, ASSISTANT = the identical, already-real <seed2>...</seed2> block. No new content is invented -- this only swaps which side of an existing real pair is the prompt vs. the target, mirroring the same precedent already applied to EmpathicRobotics/synth-llava v5 (Huu, Discord: "seed2 is bidirectional").

Explicitly NOT done in this pass (by design, not oversight): no new Conversation/Complex-reasoning task types requiring inference beyond the raw fields (would need either an LLM or fabricated content -- deferred to a downstream SFT stage, same call already made for harmony4d/synth_llava), no revival of the dropped base64 turn, no invented audio content for a text->listen reverse task on the timestamped family (no real transcript-to-audio mapping exists to swap).

Fixes carried over from v5 (unchanged, see prior release notes for detail)

1. <see>/</see> wrapper fix. MV-Omni's own image-block convention wraps <seed2_N> payload tokens in <see>...</see>, which was never registered as an atomic special token (previous releases silently fell back to broken multi-piece BPE text for the wrapper tag). Renamed to the already-atomic <seed2>/</seed2> wrapper used by every other source.
2. Degenerate base64 turn dropped. MV-Omni's image-description records contain a 3-turn structure, one of which ("Give me the base64 encoding for this scene" -> a raw base64 blob) is not a learnable instruction -- this turn is dropped (~6% of turns), keeping the two real turns (image description + narration).
3. (v4, 2026-07-31) USER:/ASSISTANT: reformat bugs fixed. The v3 release's turn-splitting had two bugs affecting 64% of records combined: (a) records with a YouTube-metadata/caption preamble before the first Q: (30% of records) were left completely unconverted -- no USER:/ASSISTANT: markers at all; (b) turn-splitting required a literal "\nA: " (space after the colon), but a plain majority of real answer markers in this source have no space ("\nA:"), so those turns' real answer text was merged into the question half, leaving ASSISTANT: empty (34% of records). Both fixed with regex-based boundary matching (\s* instead of a required literal space) plus folding any preamble into the first turn's USER: side. Real content recovered: 9,654,544 real turns kept post-fix vs. ~1.7M for the same record count under the buggy v3 script (9-10x more real content).
4. (v5, 2026-08-02) <speak> never appears in a USER: turn. Per project design rule (the assistant listens and speaks; the user only ever listens), any <speak>-tagged audio block found inside a USER: ... ASSISTANT: span (a side effect of the v4 preamble-fold fix above, which could fold a raw <speak>-tagged preamble segment into the first turn's USER side) is downsampled to <listen> format in place (7 tok/frame -> 3 tok/frame: keep L0/L1a/L1b, drop the 4 L2 sub-bands -- mathematically exact, no re-encoding). <speak> legitimately on the ASSISTANT side (this source's own listen->transcribe->speak turn family) is untouched. Verified over the full corpus: 0 occurrences of <speak> inside any USER span post-fix (was present in ~13.8% of records pre-fix, consistent across all 6 shards).

On top of those fixes, the Q:/A: convention used previously is rewritten as USER:/ASSISTANT: per turn (this source is genuinely multi-turn, not single Q/A), and an empty <think>\n</think> pair is added before every assistant turn -- consistent with the other 5 sources in the training mix.

Separately (not part of this text-format pass, but relevant to anyone retokenizing this release): the previous MV-Omni tokenize predated the vocab's <listen>/<speak>/SNAC-L2-band additions, so a large fraction of <speak> audio payload silently fell back to broken multi-piece BPE text. That is a tokenizer-time issue, not present in this raw text release, but worth knowing if you tokenize this data with an older tokenizer checkpoint.

Format

USER: <prompt> ASSISTANT:
<think>
</think>
<seed2>...</seed2> / <listen>...</listen> / <speak>...</speak> (per turn, depending on modality)

Columns: id (new, v6), text, metadata (unchanged since v3), task (new, v6 -- see item 3 above).

Base

MixtureVitae-Omni, re-tokenized with tokenizer_vla_qwen3_v2.