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Paper Citation Record · LEDGER

Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2405.13326.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2405.13326 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:59:38.798407Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-22T17:41:53.132989Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d05871aa-93ec-402f-ae13-8b42000b262c · inbound

MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness cites this paper.

MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-16T04:59:38.798407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:59:38.798407Z digest=sha256:75c95a9b0db691fa07b848f9582123df780090538e6a7389cd1c366b4d4f18cd

Observation f3a1ab00-b309-47d8-8244-28568420b214 · inbound

Visual Compositional Tuning cites this paper.

Visual Compositional Tuning Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-22T17:41:53.136963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-22T17:39:09.890605Z digest=sha256:b346a407ed20e5e587d35d990927d30bda52d34e620739c1eef756a8ccf83cb2

Observation 6af645dc-ff40-49b0-a71a-43f22fe11a03 · inbound

What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding cites this paper.

What makes Reasoning Models Different? Follow the Reasoning Leader for Efficient Decoding Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T05:52:18.377193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:52:18.377193Z digest=sha256:c21617da7ef958b1a4fea06eae73a3039017c22792b7a21faa77aca3f162e6bf

Observation c1e42311-8a91-4ae1-8612-00412c6285e7 · inbound

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning cites this paper.

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T18:39:18.737505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T18:39:18.737505Z digest=sha256:c2b736036108ae7fa0e56a65822b3086a99d4a959d081cec2196528acdfbcb0e

Observation 2976cbe7-3fa3-4259-a0e5-efffc3808660 · inbound

UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations cites this paper.

UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversations Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T18:53:26.835834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:53:26.835834Z digest=sha256:fd3baf257ef4c9d7a010660054c30273fc0e5740581b74be2e554838909e6487

Observation fbf33416-9f5c-453b-89b2-20a4bfe2f7ac · inbound

REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once cites this paper.

REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T17:35:31.498612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:35:31.498612Z digest=sha256:6d96e56ef816bf9945a86e8361b11f83292d1327d2236ad4034aab056dd4eefa

Observation f0d1c850-79d1-4bb1-9ba3-42628e79beb4 · inbound

Gaze-to-text Generation: Beyond Categorical Decoding of Human Attention cites this paper.

Gaze-to-text Generation: Beyond Categorical Decoding of Human Attention Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning

Reference 36

Resolution
unresolved
no resolver link, observed 2026-07-31T23:36:26.346122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:36:26.346122Z digest=sha256:1c589db6cf62be748de1ad0b2d2713e834d193f10e36e437fa70da96675413ad

Observation 5af0fee8-8d3e-450b-b662-ac654ac2d455 · inbound

LLMRouter: Unified Infrastructure for Developing, Evaluating, and Deploying LLM Routers cites this paper.

LLMRouter: Unified Infrastructure for Developing, Evaluating, and Deploying LLM Routers Mosaic-IT: Cost-Free Compositional Data Synthesis for Instruction Tuning

Reference 126

Resolution
unresolved
no resolver link, observed 2026-08-15T14:34:14.255480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:34:14.255480Z digest=sha256:db06969c54d49be66d08bb5162c891c8d36c96d15daf376bcf32077224120e4d