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Paper Citation Record · LEDGER

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

As of 9 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 11 inbound Pith citation observations for arXiv:2506.11672.

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

pith.paper-citation-record.v1
2506.11672 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:09:31.323766Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:40:20.613277Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T23:26:23.175930Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact1
  • verified fuzzy9
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e7deeb41-7e8f-4733-b52e-5c013f3821f3 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 6

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Observation 927f035b-2bee-4582-9dcb-55fb6ccceaf5 · outbound

This paper cites Higher Layers Need More LoRA Experts.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Higher Layers Need More LoRA Experts

Reference 7

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Observation d121950c-74a0-4677-b63c-8878a46a361e · outbound

This paper cites an unresolved cited work.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Unresolved cited work

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8a19a04d-3c44-432e-894f-9a99e5135f38 · outbound

This paper cites Llaca: Multimodal large language continual assistant.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Llaca: Multimodal large language continual assistant

Reference 11

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Observation e8070477-22a8-4078-9e16-777e1355326e · outbound

This paper cites Alphalora: Assigning lora experts based on layer training quality.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Alphalora: Assigning lora experts based on layer training quality

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 5fb42835-dcd5-4050-ba1c-2ce4760570f3 · outbound

This paper cites an unresolved cited work.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Unresolved cited work

Reference 13

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raw_fallback, observed 2026-08-07T04:09:33.372968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:09:30.099489Z digest=sha256:f6f97f0c35adac6adc27a55a0e12bbeddff45e769b463686e2cbd2d2d8af4c18

Observation 1c889673-1bb4-41c0-8cde-b067de7deca9 · outbound

This paper cites ConPET: Continual Parameter-Efficient Tuning for Large Language Models.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning ConPET: Continual Parameter-Efficient Tuning for Large Language Models

Reference 16

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Observation d75023ed-f923-46e5-a9c8-6d56d4c6dcf6 · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 17

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source=pdf_text observed=2026-08-07T04:09:30.458721Z digest=sha256:6459b4ddffdd68ea4af2bac549480be1472aba30c8b02494adb901527f56d697

Observation cced0ed5-a749-4d15-8551-4987389ecbdc · outbound

This paper cites Orthogonal subspace learning for language model continual learning.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Orthogonal subspace learning for language model continual learning

Reference 18

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source=pdf_text observed=2026-08-07T04:09:30.535440Z digest=sha256:97b18b56995027cf70996d4fca405d803bbc797393c38e8160f00d5aeff69b51

Observation 6e7dc6d7-574c-4760-bc1e-89969a74e542 · outbound

This paper cites SMoLoRA: Exploring and Defying Dual Catastrophic Forgetting in Continual Visual Instruction Tuning.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning SMoLoRA: Exploring and Defying Dual Catastrophic Forgetting in Continual Visual Instruction Tuning

Reference 19

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source=pdf_text observed=2026-08-07T04:09:30.636693Z digest=sha256:9f08ee80cc4fd44f0702a1a0eb58f63c48f62bc1150a88e309f4d9453e496485

Observation 83585115-ece6-457b-a812-ab0a24d95450 · outbound

This paper cites Beyond Anti-Forgetting: Multimodal Continual Instruction Tuning with Positive Forward Transfer.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Beyond Anti-Forgetting: Multimodal Continual Instruction Tuning with Positive Forward Transfer

Reference 20

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:09:30.693896Z digest=sha256:52402684fccc0c2386ad1f2b8b23461b48ebee4eb418e6529dfa358dac9e826f

Observation 2193e504-0396-4d27-8390-f69c30c0412f · outbound

This paper cites InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:09:30.755791Z digest=sha256:bcd4a3d1b890956b3c44c3433d906823f0045c3d559bea23a99cd950fcc6c9df

Observation 177289e8-494c-4046-b319-752a30d0124e · outbound

This paper cites By combining LLMs with multimodal encoders, they support tasks such as image captioning and visual question answering.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning By combining LLMs with multimodal encoders, they support tasks such as image captioning and visual question answering

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T04:09:32.826530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 1626102d-d880-42fc-950f-e5e22c476ccf · outbound

This paper cites Model expansion increases capacity to handle new tasks while preserving prior information.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Model expansion increases capacity to handle new tasks while preserving prior information

Reference 25

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raw_fallback, observed 2026-08-07T04:09:32.667867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:09:31.001568Z digest=sha256:11839de6896c56fa73fa6ea91f6df316f222ea40592dcfd15a2d4a3a2f63eb90

Observation e5d4cb06-093d-446e-b7ed-41d1b198ed25 · outbound

This paper cites Recent research has extended the Mixture of Experts (MoE) framework (Jacobs et al., 1991; Shazeer et al.,.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Recent research has extended the Mixture of Experts (MoE) framework (Jacobs et al., 1991; Shazeer et al.,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T04:09:32.512818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 25e0306e-ecb4-41c8-9ea2-40608c224f17 · outbound

This paper cites These models are called Mixture of LoRA Experts (MoLE).

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning These models are called Mixture of LoRA Experts (MoLE)

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-07T04:09:32.377985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:09:31.172018Z digest=sha256:35d9f47134c064ad72d240050d8d38c6a5cc92594df5caf254b0f4381cab773f

Observation 7f46e54b-5a69-4de2-aa27-be8b47dcba01 · outbound

This paper cites Recently, curriculum learning is also widely adopted in LLMs’ pretraining process, e.g., Kimi K1.5 (Team et al., 2025), DeepSeek-Prover-V2 (Ren et al., 2025), Seed-Coder.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Recently, curriculum learning is also widely adopted in LLMs’ pretraining process, e.g., Kimi K1.5 (Team et al., 2025), DeepSeek-Prover-V2 (Ren et al., 2025), Seed-Coder

Reference 28

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation fa9b2bf0-68be-4265-b477-0dabdce1c0c0 · outbound

This paper cites an unresolved cited work.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Unresolved cited work

Reference 128

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ac58083a-d904-4748-a9b7-e61c4db7b964 · outbound

This paper cites PMoE: Progressive Mixture of Experts with Asymmetric Transformer for Continual Learning.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning PMoE: Progressive Mixture of Experts with Asymmetric Transformer for Continual Learning

Reference 1991

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Observation f6282684-f70b-4a05-9150-df55278f0b47 · outbound

This paper cites adaptability and its capacity to maintain performance on previous tasks while learning new ones.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning adaptability and its capacity to maintain performance on previous tasks while learning new ones

Reference 2014

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 83566a4e-e947-4855-b2e7-067d96b1a93f · outbound

This paper cites DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

Reference 2017

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Observation 4c35ef6f-fd57-458f-a913-65de4f2c18d9 · outbound

This paper cites Qwen2.5-VL Technical Report.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Qwen2.5-VL Technical Report

Reference 2018

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source=pdf_text observed=2026-08-07T04:09:28.516048Z digest=sha256:3cbec9501fbca7287ace9765be0c00b158c890a5b33b3e3a8c8df48d80686279

Observation 7b61919e-e07b-46fa-95d6-ddb0cac35d78 · outbound

This paper cites Progressive Neural Networks.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Progressive Neural Networks

Reference 2019

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source=pdf_text observed=2026-08-07T04:09:30.273502Z digest=sha256:4a6b36327b004966e9a42d25bfc0038f0d5bb9aad02dcc601e01df6f725adb1e

Observation fbbd6491-6ad2-4997-b957-51fb5f8e4fab · outbound

This paper cites Continual Instruction Tuning for Large Multimodal Models.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Continual Instruction Tuning for Large Multimodal Models

Reference 2020

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source=pdf_text observed=2026-08-07T04:09:29.746045Z digest=sha256:b1581f1191b117ce2a86f89168745cfd500208aff5e575114dae620575499f36

Observation c172d1c2-8a7b-4d46-9e93-fe69f94abed5 · outbound

This paper cites X., and Wen, J.-R.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning X., and Wen, J.-R

Reference 2021

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 50355626-aa5a-4faf-a6bd-96aecdeefd26 · outbound

This paper cites Continual LLaVA: Continual Instruction Tuning in Large Vision-Language Models.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Continual LLaVA: Continual Instruction Tuning in Large Vision-Language Models

Reference 2022

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no resolver link, observed 2026-08-07T04:09:28.944631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:09:28.944631Z digest=sha256:0e681490c6d1f9d956a4239df56fdd0da03582c5fde887d8cc082545451ecce8

Observation b79c439d-6923-4cc1-91c7-8ce6369cbcdf · outbound

This paper cites Loramoe: Alleviating world knowledge forgetting in large language models via moe-style plugin.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Loramoe: Alleviating world knowledge forgetting in large language models via moe-style plugin

Reference 2023

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verified fuzzy
raw_fallback, observed 2026-08-07T04:09:33.876278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation aa43eaf6-836a-4db9-adae-2533a8bb54bf · outbound

This paper cites Improving Multi-Modal Learning with Uni-Modal Teachers.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Improving Multi-Modal Learning with Uni-Modal Teachers

Reference 2024

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no resolver link, observed 2026-08-07T04:09:29.309827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 71c6daac-25de-4194-8bc4-e686916df6a1 · outbound

This paper cites Multimodal continual graph learning with neural architecture search.

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning Multimodal continual graph learning with neural architecture search

Reference 2025

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verified fuzzy
raw_fallback, observed 2026-08-07T04:09:34.020074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:09:28.696572Z digest=sha256:62801d53a97b0f9a4c8e1a240ac76511135c76c71d659af1f041593f1256d71c

Pith citing papers

Observation 96d8380d-dc7a-4d0d-83b4-111658ec0acc · inbound

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond cites this paper.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 57

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no resolver link, observed 2026-08-07T00:40:20.613277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:20.613277Z digest=sha256:e328e8c67a36b2aa1cdce9ba7b376986eb0bb3bb629009f30e02ea4717a65cf3

Observation 971d14c7-de6a-4142-bf7b-6283eb85a2bc · inbound

PASs-MoE: Mitigating Misaligned Co-drift among Router and Experts via Pathway Activation Subspaces for Continual Learning cites this paper.

PASs-MoE: Mitigating Misaligned Co-drift among Router and Experts via Pathway Activation Subspaces for Continual Learning Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 2025

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no resolver link, observed 2026-08-03T09:44:13.374266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:44:13.374266Z digest=sha256:980040162b094303d955bca4ae0bcbc2107f783b1a665b7b21ab4d59843dfb50

Observation 54e375dc-27cc-42f8-af73-c99c6c1b6e2b · inbound

CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning cites this paper.

CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 5

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verified exact
arxiv_id, observed 2026-05-11T18:36:09.042884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-08T14:57:29.592305Z digest=sha256:cc62e2f7a70e09d9eafaf20c27c263c4e6eb63911827c1211803667c4a144a6d

Observation df8d1a75-16c8-49b9-9b46-9adea920b554 · inbound

CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning cites this paper.

CRAFT: Forgetting-Aware Intervention-Based Adaptation for Continual Learning Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 5

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verified exact
arxiv_id, observed 2026-05-11T05:05:57.181381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-11T00:52:39.062539Z digest=sha256:29a768c772ab7a5415c2f459af4d4d7442d84bfb99d0e55641083dc648b134a4

Observation 1c806293-3537-4128-8293-0431fb11c850 · inbound

Hystar: Hypernetwork-driven Style-adaptive Retrieval via Dynamic SVD Modulation cites this paper.

Hystar: Hypernetwork-driven Style-adaptive Retrieval via Dynamic SVD Modulation Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 5

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verified exact
arxiv_id, observed 2026-05-12T07:06:35.281948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T03:45:05.990528Z digest=sha256:b3a9f2750afa90988524f0620fa173aa6749e2642c21d2781f75121e3e05cd6a

Observation 48b126a2-e8e8-466c-aa10-ea07180495b4 · inbound

Dynamic Cross-Modal Prompt Generation for Multimodal Continual Instruction Tuning cites this paper.

Dynamic Cross-Modal Prompt Generation for Multimodal Continual Instruction Tuning Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:21:25.225128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T03:27:45.784361Z digest=sha256:e0e7c7f7ed33ccdcace860aeb89482de3e49f1aaa772a08fd00e6da64aef6214

Observation ef3cc7d0-93ad-4226-bea9-fbffb6f64d77 · inbound

PEAM: Parametric Embodied Agent Memory through Contrastive Internalization of Experience in Minecraft cites this paper.

PEAM: Parametric Embodied Agent Memory through Contrastive Internalization of Experience in Minecraft Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T16:43:39.979877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T16:42:13.713749Z digest=sha256:969d98f48127d5fd3c318779db7edde6d1d251344ce670ee95346698d33abeb7

Observation 753c9023-14f2-4186-8f1f-3d64cbe04325 · inbound

CRAM: Centroid-Routing and Adaptive MoE for Multimodal Continual Instruction Tuning cites this paper.

CRAM: Centroid-Routing and Adaptive MoE for Multimodal Continual Instruction Tuning Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T23:26:23.177973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T14:18:11.452378Z digest=sha256:94e2b3d972a034efc854f0c8de54c09923de5c6751275505879c33b276ea9ef0

Observation 13048f2e-c9f0-43cf-9f29-d3120394c49e · inbound

ProtoAda: Prototype-Guided Adaptive Adapter Expansion and Geometric Consolidation for Multimodal Continual Instruction Tuning cites this paper.

ProtoAda: Prototype-Guided Adaptive Adapter Expansion and Geometric Consolidation for Multimodal Continual Instruction Tuning Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T22:36:17.949192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-28T15:09:00.320198Z digest=sha256:77939c230442f1db0cfa61e6703a6a08f0cc5e25fa98e94a0cf04b6fd37b9598

Observation cd576287-5c4c-4e2a-aad9-7f730f077f24 · inbound

Towards Continual Motion-Language Agents: LoRA Variants for Incremental Motion Understanding and Generation cites this paper.

Towards Continual Motion-Language Agents: LoRA Variants for Incremental Motion Understanding and Generation Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:04:28.950688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T07:36:50.034451Z digest=sha256:443543c847954969a4cf96677f1793043e72c87018db0848da6d0648200f2d17

Observation 94eb0d07-fab4-4489-b1f9-ea37fd3b5c32 · inbound

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection cites this paper.

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 19

Resolution
unresolved
no resolver link, observed 2026-07-12T06:01:58.407747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T06:01:58.407747Z digest=sha256:6a98a40cf5cf2e254fd8523e74c270c5e469e6c19143da9d7a2e73694c7cdee5