Paper Citation Record · LEDGER

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios

As of 21 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2501.11269.

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

pith.paper-citation-record.v1
2501.11269 v2

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:31:48.668387Z

measured 17 of 17 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

verified exact0
verified fuzzy8
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 410ffd95-48fd-428c-bf14-28868b2758a4 · outbound

This paper cites In this setting, the model learns and infers based on English examples, effectively leveraging the provided data.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios In this setting, the model learns and infers based on English examples, effectively leveraging the provided data

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:31:49.032691Z

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.

Observation 9aabdb95-8722-4e72-b533-d83bd00e84fe · outbound

This paper cites For example, when test- ing with Chinese data, we employ Chinese templates and Chinese examples.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios For example, when test- ing with Chinese data, we employ Chinese templates and Chinese examples

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:31:49.013248Z

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.

Observation b296e53b-369c-4e0c-9c4b-6d87c1ac8c74 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios LoRA: Low-Rank Adaptation of Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T18:31:48.549016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ad93ad4-8a1f-4946-931c-d0ce43602937 · outbound

This paper cites Speaker: Utterance.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Speaker: Utterance

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:31:48.909058Z

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.

Observation a7b7f4f8-591c-46d9-9f37-a6dbad85d8fe · outbound

This paper cites Specially, we designed three different experimental methods to validate the model’s performance variations:.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Specially, we designed three different experimental methods to validate the model’s performance variations:

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:31:49.051515Z

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.

Observation c85e41e1-3279-4b7e-b407-27e82e2a08b2 · outbound

This paper cites Dialogue History\.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Dialogue History\

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:31:48.990930Z

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.

Observation 78915d53-42f5-4757-9dbf-1690aac47f68 · outbound

This paper cites an unresolved cited work.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-10T18:31:48.969198Z

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.

Observation 0fff85ca-0352-4fdf-b35c-a62199991bb9 · outbound

This paper cites an unresolved cited work.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-10T18:31:48.951457Z

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.

Observation 5516e990-4761-4d52-8a47-9f4d0d9cc699 · outbound

This paper cites an unresolved cited work.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-10T18:31:48.932549Z

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.

Observation eb6e28af-3067-4908-868a-6991971a0e5c · outbound

This paper cites Copyright,.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Copyright,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:31:48.887710Z

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.

Observation 0a329eba-943f-4b35-9696-300040f705cf · outbound

This paper cites B.3 Data Segmentation Podcast episodes typically range from 80 to 100 utterances, making segmentation essential to gener- ate manageable samples.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios B.3 Data Segmentation Podcast episodes typically range from 80 to 100 utterances, making segmentation essential to gener- ate manageable samples

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:31:48.865552Z

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.

Observation eabe8f39-cf4a-4747-a306-f1f26126f973 · outbound

This paper cites an unresolved cited work.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-10T18:31:48.841394Z

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.

Observation e09064ad-f3d1-4e51-b05a-826d3a607b7d · outbound

This paper cites an unresolved cited work.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-10T18:31:48.818632Z

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.

Observation f0dc4379-d283-4837-9fbb-652841bdbacb · outbound

This paper cites Yeah, wel.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios Yeah, wel

Reference 17

Resolution: malformed identifier; raw_fallback, observed 2026-08-10T18:31:48.797663Z

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.

Observation 7477ed81-e0d9-433e-9c75-ed4cb2c9661e · outbound

This paper cites A Primer on Pretrained Multilingual Language Models.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios A Primer on Pretrained Multilingual Language Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T18:31:48.540942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6733951-6523-4e56-a07c-ee42b0daee51 · outbound

This paper cites In Proceedings of the 2023 Conference on Empiri- cal Methods in Natural Language Processing, pages 13244–13257, Singapore.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios In Proceedings of the 2023 Conference on Empiri- cal Methods in Natural Language Processing, pages 13244–13257, Singapore

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T18:31:49.070647Z

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.

Observation ec36a4c7-0b83-4311-8e0a-ada28d798100 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Can MLLMs Generalize to Multi-Party dialog? Exploring Multilingual Response Generation in Complex Scenarios LLaMA: Open and Efficient Foundation Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T18:31:48.557827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.