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Paper Citation Record · LEDGER

Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2410.14148.

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

pith.paper-citation-record.v1
2410.14148 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:59:32.042006Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:48:02.088369Z

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 641ebfa0-6ec9-42d1-927a-cfa270b16d45 · inbound

DAMA: Data- and Model-aware Alignment of Multi-modal LLMs cites this paper.

DAMA: Data- and Model-aware Alignment of Multi-modal LLMs Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-09T13:59:32.042006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:59:32.042006Z digest=sha256:ca19b2f07f126f4457fa0f30306a8d655ac3f9883a59ad54b77e67440a8ccb05

Observation 3b2bd443-74c9-43c1-95c7-0d44a23003f0 · inbound

From EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Reasoning-Driven Pedagogical Visualization cites this paper.

From EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Reasoning-Driven Pedagogical Visualization Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:57:37.025894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:57:37.025894Z digest=sha256:8f280db171bfd5e2af0040e54920fb4cf1b61880bd63cc3aa3db56a37b261e93

Observation ef9f6fd4-a360-4e7f-b87c-663c1ec843e9 · inbound

ASPO: Adaptive Sentence-Level Preference Optimization for Fine-Grained Multimodal Reasoning cites this paper.

ASPO: Adaptive Sentence-Level Preference Optimization for Fine-Grained Multimodal Reasoning Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:22:59.401493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:22:59.401493Z digest=sha256:d6d2a2d29a5db4588333938a02313008f1eeedd213718ce80f3e0a350c719518

Observation c272722a-afdf-4f57-af19-96d51716b24b · inbound

Zooming from Context to Cue: Hierarchical Preference Optimization for Multi-Image MLLMs cites this paper.

Zooming from Context to Cue: Hierarchical Preference Optimization for Multi-Image MLLMs Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T13:14:08.642768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:14:08.642768Z digest=sha256:249b440ca7f662d4b0c4a8248cd83f7867f2a2c903b1e84f719ebae66d6cc5df

Observation bd65fe72-c4f8-4534-8bfa-5a2cad63128d · inbound

MCA-LLaVA: Manhattan Causal Attention for Reducing Hallucination in Large Vision-Language Models cites this paper.

MCA-LLaVA: Manhattan Causal Attention for Reducing Hallucination in Large Vision-Language Models Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T18:09:04.579677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:09:04.579677Z digest=sha256:08a46f53b2b9eace8b6fd29a75e9bbd053c42b8e9b3b62155aa72e637ae7c4ae

Observation 328840b4-aa78-4058-9a84-63d740af27ce · inbound

Can Textual Reasoning Improve the Performance of MLLMs on Fine-grained Visual Classification? cites this paper.

Can Textual Reasoning Improve the Performance of MLLMs on Fine-grained Visual Classification? Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-16T14:53:00.532415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T14:51:26.368439Z digest=sha256:594a723d6d48b6463a5db5d893a6735369f68b039a4d86550ce94eb70ce679f8

Observation 91b57f47-3580-41e8-85b6-da65160b9fcd · inbound

Analyzing and Improving Fine-grained Preference Optimization in Medical LVLMs cites this paper.

Analyzing and Improving Fine-grained Preference Optimization in Medical LVLMs Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:48:02.089971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T09:52:20.508013Z digest=sha256:9d633cf20f52e851a993a9f4ea4c3c17e48df0050ebf018b878dc5062dda491a