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pith:E5JZWUAY

pith:2026:E5JZWUAYMP5JRYZTBQPZHO5G2X
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VISD: Enhancing Video Reasoning via Structured Self-Distillation

Hao Lin, Hongbo Jin, Jiayu Ding, Jingqi Tian, Kunyang Lv, Qiaoman Zhang, Xu Jiang, Zhongjing Du

Structured self-distillation with a video-aware judge improves VideoLLM reasoning accuracy and training efficiency.

arxiv:2605.06094 v4 · 2026-05-07 · cs.CV · cs.AI

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\pithnumber{E5JZWUAYMP5JRYZTBQPZHO5G2X}

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2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
Portable graph bundle live · download bundle · merged state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Experiments on diverse benchmarks show that VISD consistently outperforms strong baselines, improving answer accuracy and spatio-temporal grounding quality. Notably, VISD reaches these gains with nearly 2x faster convergence in optimization steps.

C2weakest assumption

The video-aware judge model produces diagnostically meaningful, unbiased privileged information that can be safely used for token-level supervision without introducing new failure modes or reward hacking.

C3one line summary

VISD adds structured privileged feedback from a judge model and a direction-magnitude decoupling trick to let VideoLLMs learn token-level credit assignment while keeping RL stable, yielding higher accuracy and roughly 2x faster convergence on video reasoning benchmarks.

Cited by

2 papers in Pith

Receipt and verification
First computed 2026-05-25T02:01:22.117869Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

27539b501863fa98e3330c1f93bba6d5d2f766536f0779258990c2093f428886

Aliases

arxiv: 2605.06094 · arxiv_version: 2605.06094v4 · doi: 10.48550/arxiv.2605.06094 · pith_short_12: E5JZWUAYMP5J · pith_short_16: E5JZWUAYMP5JRYZT · pith_short_8: E5JZWUAY
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/E5JZWUAYMP5JRYZTBQPZHO5G2X \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 27539b501863fa98e3330c1f93bba6d5d2f766536f0779258990c2093f428886
Canonical record JSON
{
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    "abstract_canon_sha256": "66047564e89d9049c1c3abc2e89c63810c04935c8b1b3eb8ab2084e8a2cb3c3b",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-07T12:13:15Z",
    "title_canon_sha256": "93d04c2f3cc99c20cb363f9751e2ec4788e7659aed38c0cea8dddb485f8c67e8"
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  "source": {
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    "kind": "arxiv",
    "version": 4
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}