Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:18:49.751504Z
Paper Citation Record · LEDGER
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
As of 19 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 6 inbound Pith citation observations for arXiv:2505.22694.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-15T11:44:19.622453Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T22:09:07.072600Z
Reference resolution
13 of 13 outbound references displayed
- verified exact0
- verified fuzzy5
- unresolved8
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 0d73e51b-4312-4180-8682-b3169d771374 · outbound
This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:18:49.446667Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3eae652-9928-4cb1-989f-dd89ebad1b1c · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning LLaMA: Open and Efficient Foundation Language Models
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:18:49.549628Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b531f7fc-246a-4a8c-9f1a-d1517a1eb704 · outbound
This paper cites Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, and Tuo Zhao.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, and Tuo Zhao
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:18:49.610466Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation daf23d86-60f2-4065-b2e6-519bc8e18421 · outbound
This paper cites an unresolved cited work.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T13:18:50.581970Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c2ff3e48-b9db-43c1-aa8c-119bccebd2a3 · outbound
This paper cites These datasets provide a variety of challenges that require understanding of everyday scenarios and logical reasoning.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning These datasets provide a variety of challenges that require understanding of everyday scenarios and logical reasoning
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:18:50.330148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e09ae06b-f77a-4ca7-b51c-0f4e1fd6dd0d · outbound
This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
Reference 2013
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:18:48.532229Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 652170a2-99bd-4460-9a1a-2987edbae784 · outbound
This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:18:48.973731Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 66df01bd-8632-40e1-91d1-b3c1d5853aae · outbound
This paper cites an unresolved cited work.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning Unresolved cited work
Reference 2019
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T13:18:51.234269Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation fffb81b1-b388-411d-8ab0-dadbadda76f5 · outbound
This paper cites InProceedings of the 34th International Conference on Neural Information Processing Sys- tems, pages 1877–1901.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning InProceedings of the 34th International Conference on Neural Information Processing Sys- tems, pages 1877–1901
Reference 2020
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:18:51.495809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation fdb26cfb-2a3a-4585-8666-1ba8a547c828 · outbound
This paper cites InProceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 3045–3059.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning InProceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 3045–3059
Reference 2021
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:18:50.753501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 06d8ce1c-061d-4a89-a6f1-cab1836e638d · outbound
This paper cites InProceedings of the 2022 Con- ference on Empirical Methods in Natural Language Processing, pages 6655–6672.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning InProceedings of the 2022 Con- ference on Empirical Methods in Natural Language Processing, pages 6655–6672
Reference 2022
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:18:51.848646Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation bb1b61c1-cc4c-4b9a-ad1a-20ceae8ab53e · outbound
This paper cites InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 4133–4145.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 4133–4145
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T13:18:51.034314Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 73be0b73-723e-4fd9-b6aa-d969b0420864 · outbound
This paper cites MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts.
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:18:49.328511Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation c436db0d-d2d5-400e-a280-6014667a2a94 · inbound
Rethinking Parameter Sharing for LLM Fine-Tuning with Multiple LoRAs cites this paper.
Rethinking Parameter Sharing for LLM Fine-Tuning with Multiple LoRAs MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T12:01:21.193961Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6c9a877b-c5bf-4e9c-900a-cd63f941e05c · inbound
ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics cites this paper.
ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Reference 92
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T14:28:05.261852Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18355075-1678-438e-88b5-7afc6e66e6b4 · inbound
ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics cites this paper.
ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Reference 92
- Resolution
- unresolved
- no resolver link, observed 2026-07-15T11:44:19.622453Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2832216a-43de-4021-af30-788f07c7df5c · inbound
STK-Adapter: Incorporating Evolving Graph and Event Chain for Temporal Knowledge Graph Extrapolation cites this paper.
STK-Adapter: Incorporating Evolving Graph and Event Chain for Temporal Knowledge Graph Extrapolation MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Reference 95
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T12:51:07.085176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation eadc1db4-b4ac-4d16-ab7a-62c3c885f730 · inbound
A$_3$B$_2$: Adaptive Asymmetric Adapter for Alleviating Branch Bias in Vision-Language Image Classification with Few-Shot Learning cites this paper.
A$_3$B$_2$: Adaptive Asymmetric Adapter for Alleviating Branch Bias in Vision-Language Image Classification with Few-Shot Learning MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T19:17:51.087417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ad23fc9b-6a9b-4df7-be92-eae938145bfe · inbound
A$_3$B$_2$: Adaptive Asymmetric Adapter for Alleviating Branch Bias in Vision-Language Image Classification with Few-Shot Learning cites this paper.
A$_3$B$_2$: Adaptive Asymmetric Adapter for Alleviating Branch Bias in Vision-Language Image Classification with Few-Shot Learning MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T22:09:07.075934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.