Rethinking Query Optimization for Multi-Agent Systems [Vision] | Paper Citation Record

Observation 42c1d32c-78e9-4a03-bd16-a135a31aafa7 · outbound

This paper cites LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead.

Rethinking Query Optimization for Multi-Agent Systems [Vision] LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead

Reference 1

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Observation 2ed1d7ae-5f5d-4f55-ae9b-2eceb6e50b15 · outbound

This paper cites RoCo: Dialectic Multi-Robot Collaboration with Large Language Models.

Rethinking Query Optimization for Multi-Agent Systems [Vision] RoCo: Dialectic Multi-Robot Collaboration with Large Language Models

Reference 2

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This paper cites The Twelfth International Conference on Learning Representations (ICLR) , year=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] The Twelfth International Conference on Learning Representations (ICLR) , year=

Reference 3

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This paper cites ICML , author=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] ICML , author=

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Observation 9668657f-5762-4723-812d-53798f1bba4a · outbound

This paper cites IJCAI , author=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] IJCAI , author=

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Observation 23bdd5fd-6e62-44e1-8a4e-18da4e84e314 · outbound

This paper cites NeurIPS , author=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] NeurIPS , author=

Reference 6

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Observation 42e77c4d-781b-4367-8929-37a4bb8d15c5 · outbound

This paper cites Differentiation.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Differentiation

Reference 7

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Observation 09007500-e5a2-41aa-a7ae-d88c0e59f0ac · outbound

This paper cites AutoGen: Enabling Next-Gen.

Rethinking Query Optimization for Multi-Agent Systems [Vision] AutoGen: Enabling Next-Gen

Reference 8

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Observation 7988a914-4b86-4001-919d-d01ca5aa0d71 · outbound

This paper cites The Berkeley Artificial Intelligence Research Blog , author=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] The Berkeley Artificial Intelligence Research Blog , author=

Reference 9

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Observation 6943abb4-0adc-40e1-9c77-5bef778565bd · outbound

This paper cites Gonzalez and Ion Stoica , booktitle=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Gonzalez and Ion Stoica , booktitle=

Reference 10

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Observation 2e91dddf-f502-4347-aeba-b63a7138e652 · outbound

This paper cites Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences

Reference 11

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Observation ae3f847b-2207-41d1-a206-3b1e42fff870 · outbound

This paper cites Yan and Haichen Shen and Meghan Cowan and Leyuan Wang and Yuwei Hu and Luis Ceze and Carlos Guestrin and Arvind Krishnamurthy , editor =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Yan and Haichen Shen and Meghan Cowan and Leyuan Wang and Yuwei Hu and Luis Ceze and Carlos Guestrin and Arvind Krishnamurthy , editor =

Reference 12

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Observation 904c369a-1692-47cc-8eb1-2a903a036eb0 · outbound

This paper cites CoRR , volume =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] CoRR , volume =

Reference 13

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Observation 7ba87a09-9183-463e-a633-e2e4315d8a76 · outbound

This paper cites Neurocomputing , volume =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Neurocomputing , volume =

Reference 14

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Observation 4b2379b2-d558-4b64-ad3e-962b80228104 · outbound

This paper cites ACM Computing Surveys , volume =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] ACM Computing Surveys , volume =

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Observation 0c7b0f32-2814-431a-9a24-54afd8f992c0 · outbound

This paper cites SCOPE: Stochastic and Counterbiased Option Placement for Evaluating Large Language Models.

Rethinking Query Optimization for Multi-Agent Systems [Vision] SCOPE: Stochastic and Counterbiased Option Placement for Evaluating Large Language Models

Reference 16

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Observation 6373bcc2-22a9-455a-b5a3-f9f3e9ca7265 · outbound

This paper cites AdaptFlow: Adaptive Workflow Optimization via Meta-Learning.

Rethinking Query Optimization for Multi-Agent Systems [Vision] AdaptFlow: Adaptive Workflow Optimization via Meta-Learning

Reference 17

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Observation 0a16e087-f4b2-485a-891c-93acbd42c061 · outbound

This paper cites Franklin and Bj.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Franklin and Bj

Reference 18

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Observation 79edb979-8788-4f8a-b871-d70d84886bd4 · outbound

This paper cites Advances in Neural Information Processing Systems (NeurIPS) , year =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Advances in Neural Information Processing Systems (NeurIPS) , year =

Reference 19

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Observation 69fbdc29-751e-4a98-bf47-1c094c43a6fa · outbound

This paper cites Proceedings of the International Conference on Learning Representations (ICLR) , year =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the International Conference on Learning Representations (ICLR) , year =

Reference 20

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Observation 7f79d7e0-3ae1-46bb-ab2a-c845867896fc · outbound

This paper cites Proceedings of the VLDB Endowment (PVLDB) , volume =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the VLDB Endowment (PVLDB) , volume =

Reference 21

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Observation 5123c6d7-6886-4548-b630-67c197dedcbd · outbound

This paper cites Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IPDPS) , year =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IPDPS) , year =

Reference 22

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Observation 5c4ba527-1fba-4726-9447-22edc0230f51 · outbound

This paper cites Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023) , year =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023) , year =

Reference 23

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Observation f4ca8a9f-2225-4cc9-8ae0-84d7a8b296f7 · outbound

This paper cites Bespoke OLAP: Synthesizing Workload-Specific One-size-fits-one Database Engines.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Bespoke OLAP: Synthesizing Workload-Specific One-size-fits-one Database Engines

Reference 24

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Observation 804fa36f-dfd0-4691-a1f0-678185ec46a8 · outbound

This paper cites 2026 , eprint =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] 2026 , eprint =

Reference 25

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Observation ffd15ec0-2683-4cbf-8691-54066c104429 · outbound

This paper cites Proceedings of the VLDB Endowment (PVLDB) , volume=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the VLDB Endowment (PVLDB) , volume=

Reference 26

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This paper cites Proceedings of the 38th Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL) , pages=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the 38th Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL) , pages=

Reference 27

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This paper cites Proceedings of the 12th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) , pages=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the 12th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) , pages=

Reference 28

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Observation 62e2d529-fe9c-4266-bac6-2d0b67630639 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Evaluating Large Language Models Trained on Code

Reference 29

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Observation c0b6bc50-b30e-4021-b08b-4192337db660 · outbound

This paper cites Proceedings of the International Conference on Machine Learning (ICML) , pages=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the International Conference on Machine Learning (ICML) , pages=

Reference 30

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Observation 13566d5d-9b76-426f-9f2d-075c768f9ccc · outbound

This paper cites Proceedings of the VLDB Endowment (PVLDB) , volume=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the VLDB Endowment (PVLDB) , volume=

Reference 31

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Observation f3c0730e-c85b-4733-8c99-a39eff0612f1 · outbound

This paper cites ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference Optimization.

Rethinking Query Optimization for Multi-Agent Systems [Vision] ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference Optimization

Reference 32

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Observation a351ddd9-bc28-45f7-9f56-c019c3f9d719 · outbound

This paper cites Automated Design of Agentic Systems.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Automated Design of Agentic Systems

Reference 33

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Observation bcfbd22a-cc70-4821-94e1-39bc0d9d6833 · outbound

This paper cites AutoFlow: Automated Workflow Generation for Large Language Model Agents.

Rethinking Query Optimization for Multi-Agent Systems [Vision] AutoFlow: Automated Workflow Generation for Large Language Model Agents

Reference 34

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Observation e3c5fd77-b52c-45ad-b50e-85f8b7b284bc · outbound

This paper cites arXiv preprint arXiv:2502.05957 , year=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] arXiv preprint arXiv:2502.05957 , year=

Reference 35

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Observation 5da06ae4-818f-4329-ae08-382ff6f9acd4 · outbound

This paper cites AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors.

Rethinking Query Optimization for Multi-Agent Systems [Vision] AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors

Reference 36

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Rethinking Query Optimization for Multi-Agent Systems [Vision] arXiv preprint arXiv:2502.xxxxx , year=

Reference 37

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This paper cites CIDR Conference , year=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] CIDR Conference , year=

Reference 38

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Observation e2b8fdcf-1ff6-446c-97b4-76d68e8f54eb · outbound

This paper cites PVLDB , year=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] PVLDB , year=

Reference 39

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This paper cites PVLDB , volume=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] PVLDB , volume=

Reference 40

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This paper cites 2025 , url =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] 2025 , url =

Reference 41

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Rethinking Query Optimization for Multi-Agent Systems [Vision] 2025 , month =

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Observation 0787aea0-d72b-4f36-a8ba-8c6366e47af4 · outbound

This paper cites Proceedings of the 33rd International Conference on Very Large Data Bases (VLDB) , pages =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the 33rd International Conference on Very Large Data Bases (VLDB) , pages =

Reference 43

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Observation 09f3aae2-0998-4fe6-9897-aae08098cc35 · outbound

This paper cites Foundations and Trends in Machine Learning , volume =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Foundations and Trends in Machine Learning , volume =

Reference 44

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Observation bba12bcf-d1b5-47e1-8fa1-099315f9d975 · outbound

This paper cites Dalvi and Dan Suciu , title =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Dalvi and Dan Suciu , title =

Reference 45

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Observation 3bc91c95-609a-4bc7-a664-c191f8a70054 · outbound

This paper cites Information Systems Frontiers , volume =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Information Systems Frontiers , volume =

Reference 46

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Observation 193e9de8-574e-43dc-a8e6-189b729e703b · outbound

This paper cites Frontiers Comput.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Frontiers Comput

Reference 47

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Observation b2f1bcbb-22c5-4ba9-bb27-41b3bfcd6474 · outbound

This paper cites Product Quantization for Nearest Neighbor Search , journal =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Product Quantization for Nearest Neighbor Search , journal =

Reference 48

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Observation 5d49e352-1758-44db-86a8-1dd52550e7b7 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Rethinking Query Optimization for Multi-Agent Systems [Vision] DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 49

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Observation 7103fef5-0429-4034-b07d-997bfcf1f38a · outbound

This paper cites 6th International Conference on Learning Representations,.

Rethinking Query Optimization for Multi-Agent Systems [Vision] 6th International Conference on Learning Representations,

Reference 50

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Observation 4528f756-8cd8-440c-8b66-91638430266c · outbound

This paper cites LSM-VEC: A Large-Scale Disk-Based System for Dynamic Vector Search.

Rethinking Query Optimization for Multi-Agent Systems [Vision] LSM-VEC: A Large-Scale Disk-Based System for Dynamic Vector Search

Reference 51

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This paper cites 2023 , doi =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] 2023 , doi =

Reference 52

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Observation 59b839d2-902c-43d8-86a3-39dc67c35f66 · outbound

This paper cites EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning.

Rethinking Query Optimization for Multi-Agent Systems [Vision] EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning

Reference 53

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Observation aee113da-89af-485e-9096-685fbd2ad3c7 · outbound

This paper cites CoRR , volume =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] CoRR , volume =

Reference 54

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Observation 69a83838-9593-4786-9793-83ef72036af0 · outbound

This paper cites 9th International Conference on Learning Representations,.

Rethinking Query Optimization for Multi-Agent Systems [Vision] 9th International Conference on Learning Representations,

Reference 55

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Observation 58093fe2-7e5b-4ef2-b9c2-9fb6575bbede · outbound

This paper cites Knowles and Weijie Zheng , editor =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Knowles and Weijie Zheng , editor =

Reference 56

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Observation eed07428-a724-46a7-8617-8c0a71d9fd2d · outbound

This paper cites Prefill-Decode Aggregation or Disaggregation? Unifying Both for Goodput-Optimized LLM Serving.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Prefill-Decode Aggregation or Disaggregation? Unifying Both for Goodput-Optimized LLM Serving

Reference 57

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Observation 4885bafd-1f37-47f2-8ec2-2b30e4d4e6d2 · outbound

This paper cites Unlocking Efficiency in Large Language Model Inference:.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Unlocking Efficiency in Large Language Model Inference:

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Observation adab6351-1086-4fb7-b323-c56dabed5e5e · outbound

This paper cites Deferred prefill for throughput maximization in.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Deferred prefill for throughput maximization in

Reference 59

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Observation abb20634-666c-40b9-a0bd-8ac4ce44ff94 · outbound

This paper cites DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving , booktitle =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving , booktitle =

Reference 60

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Observation b53f2a7b-8902-42c9-b215-13916d920252 · outbound

This paper cites Ilyas and Theodoros Rekatsinas and Shivaram Venkataraman , editor =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Ilyas and Theodoros Rekatsinas and Shivaram Venkataraman , editor =

Reference 61

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Observation 9eeccc7f-9915-45ea-97e7-964086884875 · outbound

This paper cites Ansor: Generating High-Performance Tensor Programs for Deep Learning , booktitle =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Ansor: Generating High-Performance Tensor Programs for Deep Learning , booktitle =

Reference 62

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Observation b5063376-663a-4af1-aca0-e05732a90343 · outbound

This paper cites 2024 , url =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] 2024 , url =

Reference 63

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Observation 50c80e75-2c52-4a62-a744-56987c147e20 · outbound

This paper cites Ilyas and Theodoros Rekatsinas and Shivaram Venkataraman , editor =.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Ilyas and Theodoros Rekatsinas and Shivaram Venkataraman , editor =

Reference 64

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Observation df876bc3-4474-4949-b163-5112ca607bd7 · outbound

This paper cites LSM-VEC: A Large-Scale Disk-Based System for Dynamic Vector Search.

Rethinking Query Optimization for Multi-Agent Systems [Vision] LSM-VEC: A Large-Scale Disk-Based System for Dynamic Vector Search

Reference 65

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Observation a2b46e7d-c2d3-4789-9f7a-ee35225677a1 · outbound

This paper cites GPT Semantic Cache: Reducing LLM Costs and Latency via Semantic Embedding Caching.

Rethinking Query Optimization for Multi-Agent Systems [Vision] GPT Semantic Cache: Reducing LLM Costs and Latency via Semantic Embedding Caching

Reference 66

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Observation de58e4f2-575e-46fc-8eec-5dfa63d53895 · outbound

This paper cites an unresolved cited work.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Unresolved cited work

Reference 67

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Observation a561b949-0e91-407e-976d-458bc09b595a · outbound

This paper cites The Twelfth International Conference on Learning Representations (ICLR) , year=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] The Twelfth International Conference on Learning Representations (ICLR) , year=

Reference 68

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Observation a0a0bbe1-85dc-46a6-b4ce-c9f10faa27fb · outbound

This paper cites The Twelfth International Conference on Learning Representations (ICLR) , year=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] The Twelfth International Conference on Learning Representations (ICLR) , year=

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:31.865753Z

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Observation fefb62c8-f6f5-4518-8bb8-a1795ae9b6e5 · outbound

This paper cites A Survey on LLM-as-a-Judge.

Rethinking Query Optimization for Multi-Agent Systems [Vision] A Survey on LLM-as-a-Judge

Reference 70

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Observation fe5cbed1-561f-45aa-9d77-6d3e921b9174 · outbound

This paper cites Towards Modeling Human-Agentic Collaborative Workflows: A BPMN Extension.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Towards Modeling Human-Agentic Collaborative Workflows: A BPMN Extension

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:32.115847Z

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Observation b2a8db5c-49ba-4196-a567-247d895727ca · outbound

This paper cites WorkTeam: Constructing Workflows from Natural Language with Multi-Agents.

Rethinking Query Optimization for Multi-Agent Systems [Vision] WorkTeam: Constructing Workflows from Natural Language with Multi-Agents

Reference 72

Resolution: verified exact; local_arxiv, observed 2026-08-03T17:23:24.764524Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8dbceb4d-b63f-469f-887f-338fb7f67e9a · outbound

This paper cites AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration.

Rethinking Query Optimization for Multi-Agent Systems [Vision] AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-03T17:23:24.642858Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0c325565-94c0-4daf-819a-aaefeb6f5b6a · outbound

This paper cites ICLR , author=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] ICLR , author=

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:32.398499Z

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Observation d1788861-09b1-437d-aa86-61bfb2305548 · outbound

This paper cites and Parameswaran, Aditya G.

Rethinking Query Optimization for Multi-Agent Systems [Vision] and Parameswaran, Aditya G

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:32.543546Z

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Observation ac37c3a2-455b-4ed7-ada3-e212ff9f5468 · outbound

This paper cites Stage: Query Execution Time Prediction in Amazon Redshift.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Stage: Query Execution Time Prediction in Amazon Redshift

Reference 76

Resolution: metadata mismatch; local_arxiv, observed 2026-08-03T17:23:24.502637Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 93a4add5-cb74-4eed-bc58-5fe0ba7ce455 · outbound

This paper cites Small Language Models are the Future of Agentic AI.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Small Language Models are the Future of Agentic AI

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:32.737599Z

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Observation 16880630-909b-4e69-a317-07912ef84265 · outbound

This paper cites Bootstrapping Learned Cost Models with Synthetic SQL Queries.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Bootstrapping Learned Cost Models with Synthetic SQL Queries

Reference 78

Resolution: metadata mismatch; local_arxiv, observed 2026-08-03T17:23:24.340829Z

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Observation 86cb7f6f-2c39-498f-b298-514ec683d3e0 · outbound

This paper cites Adapting LLMs for Structured Natural Language API Integration , url=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Adapting LLMs for Structured Natural Language API Integration , url=

Reference 79

Resolution: verified exact; doi, observed 2026-08-03T17:23:24.184957Z

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Observation 7f0e60d6-99df-47a2-b403-69f4a8987242 · outbound

This paper cites Are Bias Evaluation Methods Biased ?.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Are Bias Evaluation Methods Biased ?

Reference 80

Resolution: verified exact; local_arxiv, observed 2026-08-03T17:23:24.063374Z

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Observation 26592325-7e17-4a2b-a224-e7b1b6e6be6b · outbound

This paper cites A Learned Cost Model-based Cross-engine Optimizer for SQL Workloads.

Rethinking Query Optimization for Multi-Agent Systems [Vision] A Learned Cost Model-based Cross-engine Optimizer for SQL Workloads

Reference 81

Resolution: metadata mismatch; local_arxiv, observed 2026-08-03T17:23:23.933408Z

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Observation a2fc57e4-5fa0-4108-82c3-ca448ae25a35 · outbound

This paper cites AI Risk Atlas: Taxonomy and Tooling for Navigating AI Risks and Resources.

Rethinking Query Optimization for Multi-Agent Systems [Vision] AI Risk Atlas: Taxonomy and Tooling for Navigating AI Risks and Resources

Reference 82

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Observation b2cc8e56-416a-4acb-9875-9a2e95eef49d · outbound

This paper cites FlowMind: Automatic Workflow Generation with LLMs.

Rethinking Query Optimization for Multi-Agent Systems [Vision] FlowMind: Automatic Workflow Generation with LLMs

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:33.111803Z

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Observation bb8c9bf5-c28d-4a47-bda8-e75e8360503a · outbound

This paper cites Reducing hallucination in structured outputs via Retrieval-Augmented Generation.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Reducing hallucination in structured outputs via Retrieval-Augmented Generation

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:33.172183Z

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Observation fa1f95e3-6805-4c57-a838-09b102fd5a79 · outbound

This paper cites The Eleventh International Conference on Learning Representations (ICLR) , year=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] The Eleventh International Conference on Learning Representations (ICLR) , year=

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:33.225457Z

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Observation 3fdaef4d-3615-41d9-8fa6-943dbd775371 · outbound

This paper cites Self-planning Code Generation with Large Language Models , url=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Self-planning Code Generation with Large Language Models , url=

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:33.322379Z

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Observation bd76192b-7548-4948-8d30-602de354bbbf · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Rethinking Query Optimization for Multi-Agent Systems [Vision] The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:33.493790Z

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Observation cc4f337a-810f-402d-a61b-ad5d03247048 · outbound

This paper cites TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usage , url=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usage , url=

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:33.583119Z

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Observation 31cd550f-5708-4d32-872b-87f6a563be8d · outbound

This paper cites ICLR , author=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] ICLR , author=

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:33.743154Z

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Observation 1bd7cfdc-8a79-4d65-ad31-23f4a3af927d · outbound

This paper cites 10.48550/arXiv.2502.05957 , author=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] 10.48550/arXiv.2502.05957 , author=

Reference 90

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Observation 7fcc8542-e287-4fce-9bb7-a7122c7e2575 · outbound

This paper cites CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society.

Rethinking Query Optimization for Multi-Agent Systems [Vision] CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:34.059504Z

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Observation 9d1cc064-8616-463b-967f-5482acb6b251 · outbound

This paper cites ICLR , author=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] ICLR , author=

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:34.205732Z

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Observation c5fe9342-8a32-4498-afca-c9c09db16dd6 · outbound

This paper cites Differentiation.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Differentiation

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:34.318781Z

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Observation 8f46b5ad-4a17-4ec4-a88e-3d281acce8a6 · outbound

This paper cites Forty-first International Conference on Machine Learning (ICML) , year=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Forty-first International Conference on Machine Learning (ICML) , year=

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:34.430682Z

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Observation 708e37ce-c1c6-4bc1-90f6-84ce7f13e5fc · outbound

This paper cites A Dynamic.

Rethinking Query Optimization for Multi-Agent Systems [Vision] A Dynamic

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:34.491787Z

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Observation 00f033ae-040f-407e-b401-b2cceecace52 · outbound

This paper cites ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines.

Rethinking Query Optimization for Multi-Agent Systems [Vision] ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:34.637001Z

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Observation 541ae512-bc90-49e3-89bf-f6c41e3f15eb · outbound

This paper cites DataSciBench: An LLM Agent Benchmark for Data Science.

Rethinking Query Optimization for Multi-Agent Systems [Vision] DataSciBench: An LLM Agent Benchmark for Data Science

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:34.733190Z

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Observation ddef29b0-905d-448f-90fd-aa053c2ff138 · outbound

This paper cites Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs

Reference 98

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Observation 0b2f569a-6844-4ed0-bec3-a91077969567 · outbound

This paper cites Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP) , author=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP) , author=

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:35.019826Z

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Observation b102ea2b-786c-4674-9bc9-e7fe1541295d · outbound

This paper cites Alfonso and Martínez Cámara, Eugenio and Camacho-Collados, Jose , editor=.

Rethinking Query Optimization for Multi-Agent Systems [Vision] Alfonso and Martínez Cámara, Eugenio and Camacho-Collados, Jose , editor=

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-03T17:21:35.117582Z

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Pith citing papers