Paper Citation Record · LEDGER

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency

As of 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2607.13099.

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

pith.paper-citation-record.v1
2607.13099 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T06:36:32.688008Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

46 of 46 outbound references displayed

verified exact0
verified fuzzy0
unresolved45
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cc2e4560-a449-4b74-aa0c-2c5600559413 · outbound

This paper cites A survey of llm-based agents in medicine: How far are we from baymax? Findings of the Association for Computational Linguistics: ACL 2025, pages 10345–10359, 2025.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency A survey of llm-based agents in medicine: How far are we from baymax? Findings of the Association for Computational Linguistics: ACL 2025, pages 10345–10359, 2025

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:28.605683Z

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Observation a1d5034b-66e5-43c7-94ee-f8ef4eb9e369 · outbound

This paper cites A continued pretrained llm approach for automatic medical note generation.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency A continued pretrained llm approach for automatic medical note generation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:28.694949Z

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Observation 2094e2fa-1883-443d-b9d6-7fa05a4bbddb · outbound

This paper cites When to retrieve: Teaching llms to utilize information retrieval effectively.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency When to retrieve: Teaching llms to utilize information retrieval effectively

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:28.833968Z

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Observation 1e218023-7827-4553-bb55-9f5337858ca6 · outbound

This paper cites Large language models for information retrieval: A survey.ACM Transactions on Information Systems, 44(1):1–54, 2025.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Large language models for information retrieval: A survey.ACM Transactions on Information Systems, 44(1):1–54, 2025

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.002891Z

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Observation 1742e526-51a6-40f9-8a5b-a3ab870471a3 · outbound

This paper cites Rethinking driving world model as synthetic data generator for perception tasks.arXiv preprint arXiv:2510.19195, 2025.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Rethinking driving world model as synthetic data generator for perception tasks.arXiv preprint arXiv:2510.19195, 2025

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.083231Z

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Observation 67cf73bf-52e1-45c1-89fe-d57135fa2403 · outbound

This paper cites Adapting llms for efficient, personalized information retrieval: Methods and implications.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Adapting llms for efficient, personalized information retrieval: Methods and implications

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.226714Z

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Observation 4e9a54dd-d305-44eb-933d-eee96759e5c7 · outbound

This paper cites Competition-level code generation with alphacode.Science, 378(6624):1092–1097, 2022.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Competition-level code generation with alphacode.Science, 378(6624):1092–1097, 2022

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.359398Z

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Observation e9c906f1-e2ea-43ba-ad2e-72af807298eb · outbound

This paper cites A review on code generation with llms: Application and evaluation.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency A review on code generation with llms: Application and evaluation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.421130Z

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Observation 5aa78587-0deb-4722-af76-09d3f30e5359 · outbound

This paper cites An empirical study of retrieval-augmented code generation: Challenges and opportunities.ACM Transactions on Software Engineering and Methodology, 34(7):1–28, 2025.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency An empirical study of retrieval-augmented code generation: Challenges and opportunities.ACM Transactions on Software Engineering and Methodology, 34(7):1–28, 2025

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.501314Z

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Observation 93d43a95-f2a3-4283-929d-1b2b4ac968eb · outbound

This paper cites A survey on large language models for code generation.ACM Transactions on Software Engineering and Methodology, 35(2):1–72, 2026.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency A survey on large language models for code generation.ACM Transactions on Software Engineering and Methodology, 35(2):1–72, 2026

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.604896Z

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Observation 4e5f0e06-8ecf-4407-9692-5edef23e1693 · outbound

This paper cites Understanding the planning of LLM agents: A survey.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Understanding the planning of LLM agents: A survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.689533Z

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Observation a51bb4e5-c7b2-4a5f-96ac-b7a03215b50a · outbound

This paper cites A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.744609Z

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Observation 05cc8c2e-cb3d-4f1c-bc7d-063a51d21fa9 · outbound

This paper cites Llm agents for education: Advances and applications.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Llm agents for education: Advances and applications

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.806185Z

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Observation f6ae74fe-5d41-4724-ab53-fea1bfb75830 · outbound

This paper cites Agentswift: Efficient llm agent design via value-guided hierarchical search.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Agentswift: Efficient llm agent design via value-guided hierarchical search

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.875667Z

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Observation 53c9a75a-f6c6-4c2c-90f9-0f041908cbe0 · outbound

This paper cites Watermarking techniques for large language models: A survey.Artificial Intelligence Review, 59(2):74, 2026.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Watermarking techniques for large language models: A survey.Artificial Intelligence Review, 59(2):74, 2026

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.927657Z

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Observation 36a72cbe-59af-4ca1-ae5d-64d513e0c65c · outbound

This paper cites RLSpoofer: A Lightweight Evaluator for LLM Watermark Spoofing Resilience.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency RLSpoofer: A Lightweight Evaluator for LLM Watermark Spoofing Resilience

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:29.983182Z

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Observation 282fbd2c-401d-409f-8ed1-1eaf6555f959 · outbound

This paper cites A watermark for large language models.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency A watermark for large language models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.029445Z

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Observation b7081ee4-6cf3-45dd-acad-bdeb18050bce · outbound

This paper cites Scalable watermarking for identifying large language model outputs.Nature, 634(8035):818–823, 2024.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Scalable watermarking for identifying large language model outputs.Nature, 634(8035):818–823, 2024

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.082238Z

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Observation 98b66b4c-2ee7-4f13-81fa-170ca6e64a34 · outbound

This paper cites A survey on mixture of experts.Authorea Preprints, 2024.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency A survey on mixture of experts.Authorea Preprints, 2024

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.139856Z

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Observation 3cba2a1c-4d37-408d-b5d3-3303fcd229ee · outbound

This paper cites Llama-moe: Building mixture-of-experts from llama with continual pre-training.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Llama-moe: Building mixture-of-experts from llama with continual pre-training

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.192394Z

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Observation 96e7cac6-e0c1-4ab3-ae06-3398e3720f8e · outbound

This paper cites Deepspeed-moe: Advancing mixture-of- experts inference and training to power next-generation ai scale.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Deepspeed-moe: Advancing mixture-of- experts inference and training to power next-generation ai scale

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.260790Z

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Observation 0ed085f3-17c7-46bf-8df5-e5be689ba539 · outbound

This paper cites Mixture of Cache-Conditional Experts for Efficient Mobile Device Inference.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Mixture of Cache-Conditional Experts for Efficient Mobile Device Inference

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.322638Z

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Observation d804a408-edac-4647-b108-6b5dfed1b4bc · outbound

This paper cites DeepSeek-V3 Technical Report.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency DeepSeek-V3 Technical Report

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.376276Z

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Observation 0c31027d-c0e3-4c29-aea0-a6379b36d255 · outbound

This paper cites Qwen3 Technical Report.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Qwen3 Technical Report

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.508039Z

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Observation 38a3a1e7-e120-4788-bc82-3ff607b9bb04 · outbound

This paper cites Uni-moe: Scaling unified multimodal llms with mixture of experts.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Uni-moe: Scaling unified multimodal llms with mixture of experts.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.613138Z

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Observation 3baa96b8-c85c-4461-880b-54fa9876d103 · outbound

This paper cites An entropy-based text water- marking detection method.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency An entropy-based text water- marking detection method

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.675130Z

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Observation 2aa6f9b5-c55a-4705-8874-74b2746ffc7c · outbound

This paper cites Morphmark: Flexible adaptive watermarking for large language models.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Morphmark: Flexible adaptive watermarking for large language models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.765777Z

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Observation edb2819d-7b3d-469e-820e-1ed5bbce0141 · outbound

This paper cites Markllm: An open-source toolkit for llm watermarking.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Markllm: An open-source toolkit for llm watermarking

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:30.938625Z

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Observation f5ce8f04-face-456f-ae83-ada1b6c2093a · outbound

This paper cites Mixtral of Experts.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Mixtral of Experts

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.054830Z

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Observation 0cec6b50-8122-441e-a10e-3c55edff3b2e · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.158051Z

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Observation e7899ce4-2a3d-4622-8647-6af626768807 · outbound

This paper cites Booksum: A collection of datasets for long-form narrative summarization.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Booksum: A collection of datasets for long-form narrative summarization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.225343Z

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Observation caa7b348-e558-483c-9b00-54d13f9dfb7a · outbound

This paper cites Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.284517Z

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Observation 49124aef-92f9-47f8-abf2-ef47f58b451e · outbound

This paper cites Eli5: Long form question answering.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Eli5: Long form question answering

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.333316Z

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Observation 3a616379-e14b-4e79-bf37-9df095d728a8 · outbound

This paper cites Measuring Coding Challenge Competence With APPS.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Measuring Coding Challenge Competence With APPS

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.387288Z

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Observation 058e257c-e222-4d83-9947-6fcf996e4d58 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Training Verifiers to Solve Math Word Problems

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.493408Z

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Observation 618bce72-f5c2-45c6-b214-0e0d27200afd · outbound

This paper cites Measuring Massive Multitask Language Understanding.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Measuring Massive Multitask Language Understanding

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.585134Z

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Observation 3683cd3b-a4a2-497b-8a33-d9990aed0241 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Instruction-Following Evaluation for Large Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.724759Z

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Observation 15502691-e892-4aaa-9fda-ab244b22411e · outbound

This paper cites Writingbench: A comprehensive benchmark for generative writing.arXiv preprint arXiv:2503.05244, 2025.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Writingbench: A comprehensive benchmark for generative writing.arXiv preprint arXiv:2503.05244, 2025

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.817180Z

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Observation 78d2c0a7-44a4-4e29-8cd5-eac08b364a18 · outbound

This paper cites Robust Distortion-free Watermarks for Language Models.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Robust Distortion-free Watermarks for Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:31.896778Z

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Observation d488c09c-f30a-4193-a399-7b72961d1683 · outbound

This paper cites Unbiased Watermark for Large Language Models.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Unbiased Watermark for Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:32.028303Z

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Observation a08a0cd3-8688-43a4-bdde-a69548f56282 · outbound

This paper cites An Unforgeable Publicly Verifiable Watermark for Large Language Models.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency An Unforgeable Publicly Verifiable Watermark for Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:32.128014Z

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Observation 388477e7-441b-47e5-8da6-205cd3c237ff · outbound

This paper cites A Semantic Invariant Robust Watermark for Large Language Models.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency A Semantic Invariant Robust Watermark for Large Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:32.242481Z

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Observation 1e78ecba-5b2f-406b-9882-7e98531d4d15 · outbound

This paper cites Can watermarks survive translation? on the cross-lingual consistency of text watermark for large language models.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Can watermarks survive translation? on the cross-lingual consistency of text watermark for large language models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:32.382325Z

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Observation 12b7452a-36f4-4364-b931-349dfc7d386a · outbound

This paper cites Black-Box Detection of Language Model Watermarks.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Black-Box Detection of Language Model Watermarks

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:32.442285Z

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Observation 7c54edc6-d54e-446c-9ca6-c1db00493d4d · outbound

This paper cites Semstamp: A semantic watermark with paraphrastic robustness for text generation.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Semstamp: A semantic watermark with paraphrastic robustness for text generation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-02T06:36:32.588326Z

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Observation 37426aa8-3e7e-470c-8ef3-c2fe86afb6f3 · outbound

This paper cites Global Prompt.

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency Global Prompt

Reference 46

Resolution: malformed identifier; no resolver link, observed 2026-08-02T06:36:32.688008Z

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Pith citing papers

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