Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning | Paper Citation Record

Observation c7daca19-df08-4588-9b6f-5c175c519bc6 · outbound

This paper cites Introducing gpt-5,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Introducing gpt-5,

Reference 1

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Observation 40464fdf-d3b8-4e8e-aacb-9b01b8365e83 · outbound

This paper cites The Llama 3 Herd of Models.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning The Llama 3 Herd of Models

Reference 2

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Observation 772c3f2e-6c36-4cac-a620-d6ed33f244c7 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 3

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Observation d296791c-8c1e-4122-b7ed-e9b79f878995 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 4

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Observation 2c2d80f2-c84c-4c00-bbb6-0818b3556ef8 · outbound

This paper cites Reading Wikipedia to Answer Open-Domain Questions.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Reading Wikipedia to Answer Open-Domain Questions

Reference 5

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Observation 0b82f92b-3fc4-4018-b6ab-8a055cb0949e · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 6

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Observation 3ff3292d-6f10-4e96-803d-71e34af85ec9 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Dense Passage Retrieval for Open-Domain Question Answering

Reference 7

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Observation 056ed0df-42d8-4cc7-b69e-7544d1ac3857 · outbound

This paper cites Neural approaches to conversational ai: Question answering, task-oriented dialogues and social chatbots,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Neural approaches to conversational ai: Question answering, task-oriented dialogues and social chatbots,

Reference 8

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Observation f9eda9b8-1199-4003-8cf7-8eb7561a6aab · outbound

This paper cites Establishing and maintaining long-term human-computer relationships,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Establishing and maintaining long-term human-computer relationships,

Reference 9

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Observation bf78b49d-0123-4969-82f0-9dc91b0718bd · outbound

This paper cites GenAIPABench: A Benchmark for Generative AI-based Privacy Assistants.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning GenAIPABench: A Benchmark for Generative AI-based Privacy Assistants

Reference 10

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Observation 04b4a209-a1f9-4284-b2c2-e9b5688c6a2c · outbound

This paper cites The rising costs of training frontier AI models.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning The rising costs of training frontier AI models

Reference 11

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Observation 70e78a88-83ac-4480-9e4d-7ab33290072c · outbound

This paper cites Energy and policy considerations for deep learning in NLP,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Energy and policy considerations for deep learning in NLP,

Reference 12

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Observation 336a890d-19bc-4214-a4c4-69f841119a69 · outbound

This paper cites The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink

Reference 13

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Observation 442a240d-db6e-4bb6-ad29-77244eceb6cb · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Chain-of-thought prompting elicits reasoning in large language models,

Reference 14

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Observation fa52fd15-179c-4f45-8246-9dbe3fc2659a · outbound

This paper cites Measuring short-form factuality in large language models,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Measuring short-form factuality in large language models,

Reference 15

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Observation f1f1892b-688b-41de-9c5c-4de407a05089 · outbound

This paper cites When One LLM Drools, Multi-LLM Collaboration Rules.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning When One LLM Drools, Multi-LLM Collaboration Rules

Reference 16

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Observation 6c1b5ccb-3a98-4322-8660-49e82b0caae0 · outbound

This paper cites Ensemble methods in machine learning,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Ensemble methods in machine learning,

Reference 17

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Observation a7508b28-4e4d-47de-a288-7f8fa8092598 · outbound

This paper cites Prompt design and engineering: Introduction and advanced methods,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Prompt design and engineering: Introduction and advanced methods,

Reference 18

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Observation 2695c6a1-5bc4-425b-980d-4e87f1d52d05 · outbound

This paper cites Reducing hallucinations in large language models: A consensus voting approach using mixture of experts,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Reducing hallucinations in large language models: A consensus voting approach using mixture of experts,

Reference 19

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Observation 480115d9-467e-4f0b-9d40-29f3dd596766 · outbound

This paper cites Uncertainty-Aware Fusion: An Ensemble Framework for Mitigating Hallucinations in Large Language Models.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Uncertainty-Aware Fusion: An Ensemble Framework for Mitigating Hallucinations in Large Language Models

Reference 20

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Observation 42958fc3-d9e3-4267-a06b-abbfc2a90ab8 · outbound

This paper cites LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 21

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Observation 3fccd97e-ab86-47db-b43a-feda34dd6ba0 · outbound

This paper cites [Online].

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning [Online]

Reference 22

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Observation 304f70f3-dc84-4131-90ce-1e3502168240 · outbound

This paper cites Palimpzest: Optimizing AI-powered analytics with declarative query processing,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Palimpzest: Optimizing AI-powered analytics with declarative query processing,

Reference 23

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Observation 46a219a2-3cdb-406d-b4d9-036d1cabc91d · outbound

This paper cites Bao: Making learned query optimization practical,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Bao: Making learned query optimization practical,

Reference 24

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Observation ed7dc210-3da7-4cc9-8643-6caf48bd4a17 · outbound

This paper cites Cardinality estimation in dbms: a comprehensive benchmark evaluation,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Cardinality estimation in dbms: a comprehensive benchmark evaluation,

Reference 25

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Observation c8facb7d-544f-49f6-a8c4-d365c41f555f · outbound

This paper cites A Query Optimization Method Utilizing Large Language Models.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning A Query Optimization Method Utilizing Large Language Models

Reference 26

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Observation 3e9382f4-67c7-45eb-9215-16897a814234 · outbound

This paper cites Lero: A learning-to-rank query optimizer,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Lero: A learning-to-rank query optimizer,

Reference 27

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This paper cites Dspy: Compiling declarative language model calls into self-improving pipelines,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Dspy: Compiling declarative language model calls into self-improving pipelines,

Reference 28

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Observation 39f3577f-b0ee-4419-9dd3-58d07cd7a8db · outbound

This paper cites Frugalgpt: How to use large language models while reducing cost and improving performance,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Frugalgpt: How to use large language models while reducing cost and improving performance,

Reference 29

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Observation 126ef2f8-33b5-4d09-aa76-2b40fab99027 · outbound

This paper cites LLM-TOPLA: Efficient LLM Ensemble by Maximising Diversity.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning LLM-TOPLA: Efficient LLM Ensemble by Maximising Diversity

Reference 30

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Observation 3a6eed1d-6301-41ab-b35d-65e6fb1e971a · outbound

This paper cites Thriftllm: On cost-effective selection of large language models for classification queries,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Thriftllm: On cost-effective selection of large language models for classification queries,

Reference 31

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Observation 1dab3295-76bd-493a-8e78-956d4c549b19 · outbound

This paper cites Towards Optimizing the Costs of LLM Usage.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Towards Optimizing the Costs of LLM Usage

Reference 32

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Observation d3b7b4b9-059a-4bcf-a0d7-83374683a12b · outbound

This paper cites Querying large language models with sql,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Querying large language models with sql,

Reference 33

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This paper cites Abacus: A cost-based optimizer for semantic operator systems,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Abacus: A cost-based optimizer for semantic operator systems,

Reference 34

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Observation 63c41dc3-9de6-47c8-958c-682af25f8f98 · outbound

This paper cites The stretto execution engine for llm-augmented data systems,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning The stretto execution engine for llm-augmented data systems,

Reference 35

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Observation 18144bba-04ab-4d44-ad1a-da0acc8094d1 · outbound

This paper cites Does size matter? on the influence of ensemble size on constructing ensembles of dispatching rules,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Does size matter? on the influence of ensemble size on constructing ensembles of dispatching rules,

Reference 36

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Observation 9c866fdd-c371-4ed2-8d9c-ad5fbd0f9714 · outbound

This paper cites ML.ENERGY leaderboard,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning ML.ENERGY leaderboard,

Reference 37

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Observation 24042e4d-6c12-4318-b7de-2a57e16b9a4a · outbound

This paper cites A fast and elitist multiobjective genetic algorithm: Nsga-ii,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning A fast and elitist multiobjective genetic algorithm: Nsga-ii,

Reference 38

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This paper cites Opti-q extended version,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Opti-q extended version,

Reference 39

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Observation 7c9334c4-4d20-4989-94e0-86f8baab13d0 · outbound

This paper cites Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training

Reference 40

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Observation 4549846a-b386-4439-92e2-cde59c61eb44 · outbound

This paper cites A fast randomized algorithm for multi- objective query optimization,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning A fast randomized algorithm for multi- objective query optimization,

Reference 41

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Observation 9066f999-48bb-4831-b170-b77c48ed8977 · outbound

This paper cites [Online].

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning [Online]

Reference 42

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Observation d41f6094-d82f-4a21-a6b5-0694840d7b59 · outbound

This paper cites ChatQA: Surpassing GPT-4 on Conversational QA and RAG.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning ChatQA: Surpassing GPT-4 on Conversational QA and RAG

Reference 43

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Observation 88ea943a-8d7b-46bf-9716-71f2399f0a5f · outbound

This paper cites Qwen3 Technical Report.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Qwen3 Technical Report

Reference 44

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This paper cites Phi-4 Technical Report.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Phi-4 Technical Report

Reference 45

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Observation e187a45a-2668-4844-b66a-ef3cf3c9c12c · outbound

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Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Mistral 7B

Reference 46

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Observation 82bd6bb1-4669-4586-b694-f65485a91c5a · outbound

This paper cites Benchmarking llms via uncertainty quantification,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Benchmarking llms via uncertainty quantification,

Reference 47

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Observation 4cd1d4c6-f912-4815-98bc-a4604be401cb · outbound

This paper cites BERTopic: Neural topic modeling with a class-based TF-IDF procedure.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning BERTopic: Neural topic modeling with a class-based TF-IDF procedure

Reference 48

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Observation ad337888-a176-4f4e-bf63-3a4c6eab915a · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 49

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Observation 572d4b1a-f6dd-4db0-b07b-2b7ae8ccbb8c · outbound

This paper cites hdbscan: Hierarchical density based clustering.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning hdbscan: Hierarchical density based clustering

Reference 50

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Observation 89e1afb2-c132-4cb3-96f3-2c1be1101fd4 · outbound

This paper cites Large lan- guage models are zero-shot reasoners,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Large lan- guage models are zero-shot reasoners,

Reference 51

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Observation 2a147653-42b8-4481-a856-8a3f517a6240 · outbound

This paper cites Language mod- els are few-shot learners,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Language mod- els are few-shot learners,

Reference 52

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Observation 75ddf24c-0946-4ead-8696-2c995f01a9bd · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Bleu: a method for automatic evaluation of machine translation,

Reference 53

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Observation 36fe29f5-b1d2-4a92-a581-0c423108ac99 · outbound

This paper cites ROUGE: A package for automatic evaluation of summaries,.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning ROUGE: A package for automatic evaluation of summaries,

Reference 54

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Observation 80b9415c-bd4a-4c9b-b9b7-88b8dc7a352c · outbound

This paper cites Harnessing Multiple Large Language Models: A Survey on LLM Ensemble.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning Harnessing Multiple Large Language Models: A Survey on LLM Ensemble

Reference 55

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Observation dc627731-fd93-4eb2-961d-98424c411da5 · outbound

This paper cites FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 2023

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