Paper Citation Record · LEDGER

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations

As of 16 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 2 inbound Pith citation observations for arXiv:2505.23121.

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

pith.paper-citation-record.v1
2505.23121 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:56:45.083869Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:56:44.139662Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T15:07:03.943418Z

Reference resolution

16 of 16 outbound references displayed

verified exact0
verified fuzzy6
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 39eb7bad-7e14-4a37-b432-a3ba92efe39a · outbound

This paper cites To further expand the capabilities of large language models, multi-modal models are developed to in- corporate various types of input beyond text.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations To further expand the capabilities of large language models, multi-modal models are developed to in- corporate various types of input beyond text

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:56:46.288581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 042632f9-227d-48b1-a99f-1d6aafaba300 · outbound

This paper cites an unresolved cited work.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:56:46.018188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ec812042-398a-4186-89c5-39076d662674 · outbound

This paper cites The first part comprises the data used for training, including multi-modal pretraining and instruction tuning.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations The first part comprises the data used for training, including multi-modal pretraining and instruction tuning

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:56:45.915927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation af2a5c7d-82d0-4f5d-90c7-866643a5b361 · outbound

This paper cites Statistics show that dialogues in TMDialog are much longer, with more relevant questions and answers, than other datasets.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations Statistics show that dialogues in TMDialog are much longer, with more relevant questions and answers, than other datasets

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:56:46.160579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 59980d4c-04ee-4f79-a176-d0aaa23b871e · outbound

This paper cites Experimental Setup During the pre-training and fine-tuning phases, we execute a total of 40,000 and 10,000 training itera- tions, respectively.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations Experimental Setup During the pre-training and fine-tuning phases, we execute a total of 40,000 and 10,000 training itera- tions, respectively

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:56:45.670532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 7e6c37bc-011f-4b5b-aed4-3af9d028278f · outbound

This paper cites an unresolved cited work.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:56:45.768378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation be50690c-f9fa-400e-a3ee-2fc800bc2d10 · outbound

This paper cites We intro- duce a method that effectively utilizes the GPT-4 API for multi-modal multi-turn dialogue data gen- erating.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations We intro- duce a method that effectively utilizes the GPT-4 API for multi-modal multi-turn dialogue data gen- erating

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:56:45.313019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation de84d191-a7c3-4199-bb90-ee50ebbc5a4f · outbound

This paper cites While we applied prompt en- gineering techniques and performed data filtering andmodification,itispossiblethatsomelow-quality dialogues remain in the resulting dataset.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations While we applied prompt en- gineering techniques and performed data filtering andmodification,itispossiblethatsomelow-quality dialogues remain in the resulting dataset

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:56:45.437717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 605d3b08-b56e-45ca-a171-22c35b1ff878 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T12:56:44.677381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3893c571-7756-419b-a713-d39188771d29 · outbound

This paper cites Addressing Some Limitations of Transformers with Feedback Memory.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations Addressing Some Limitations of Transformers with Feedback Memory

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:56:44.790395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a2f0c2b-c766-4e57-b8e3-b7387a072e7c · outbound

This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations The Curse of Recursion: Training on Generated Data Makes Models Forget

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:56:44.958460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 807fbcf5-bb4d-4d4c-ae49-df28125ce891 · outbound

This paper cites MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:56:45.083869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a3f4199-17f5-434f-bf6d-41922d510f10 · outbound

This paper cites Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-07T12:56:44.868908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a6a28ac-9720-4e62-adf8-f5cd80f3dc34 · outbound

This paper cites Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T12:56:44.719903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67dff097-a4ef-4016-8731-8c3e97a36b34 · outbound

This paper cites ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T12:56:44.139662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b97d02d6-97ab-4242-a303-e1dcd79285c4 · outbound

This paper cites HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face.

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T12:56:44.913208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 67dff097-a4ef-4016-8731-8c3e97a36b34 · inbound