Pith Number

pith:DWT2XANH

pith:2026:DWT2XANHCKBJC72665A4EUJWDL

not attested not anchored not stored refs pending

MTA: Multi-Granular Trajectory Alignment for Large Language Model Distillation

Linh Ngo Van, Pham Khanh Chi, Quoc Phong Dao, Thanh Hong Nguyen, Thuat Nguyen, Trung Le

Multi-granular trajectory alignment improves knowledge distillation by matching teacher and student representations at word level in lower layers and phrase level in higher layers.

arxiv:2605.01374 v2 · 2026-05-02 · cs.CL

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\usepackage{pith}
\pithnumber{DWT2XANHCKBJC72665A4EUJWDL}

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Record completeness

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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

MTA consistently outperforms state-of-the-art baselines on standard benchmarks, with ablations confirming the contribution of each component.

C2weakest assumption

That aligning teacher and student representations along their layer-wise transformation trajectory using a layer-adaptive multi-granular strategy (word-level lower, phrase-level higher) will better guide the student to capture the teacher's internal relational structure than fixed-layer or token-level methods.

C3one line summary

MTA improves LLM knowledge distillation by aligning representations along layer-wise trajectories with adaptive granularity from words to phrases using dynamic structural and hidden representation alignment losses.

Receipt and verification

First computed	2026-06-03T01:05:50.830716Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

1da7ab81a71282917f5ef741c251361af80bd16acabf1112ad0d1860bd263913

Aliases

arxiv: 2605.01374 · arxiv_version: 2605.01374v2 · doi: 10.48550/arxiv.2605.01374 · pith_short_12: DWT2XANHCKBJ · pith_short_16: DWT2XANHCKBJC726 · pith_short_8: DWT2XANH

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/DWT2XANHCKBJC72665A4EUJWDL \
  | 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: 1da7ab81a71282917f5ef741c251361af80bd16acabf1112ad0d1860bd263913

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4a209011ec524ab89114606c2795774c10a891a1e4d1f64f66f42de78d4ce61e",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-05-02T10:52:49Z",
    "title_canon_sha256": "1b270c6c37c74de47904b5efb3f575514dfda75bb956d0009de8d7354a426b05"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.01374",
    "kind": "arxiv",
    "version": 2
  }
}