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CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval

https://doi.org/10.1145/3678880
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4471-0793-4openalex-snapshot
Combining Artificial Neural Nets
inferredcites →https://doi.org/10.1007/978-1-4471-0793-4_6openalex-snapshot
Linear and Order Statistics Combiners for Pattern Classification
inferredcites →https://doi.org/10.1007/978-3-031-02181-7openalex-snapshot
Pretrained Transformers for Text Ranking
inferredcites →https://doi.org/10.1007/978-3-031-43415-0_37openalex-snapshot
MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders Are Better Dense Retrievers
inferredcites →https://doi.org/10.1007/978-3-031-44693-1_47openalex-snapshot
Mixture-of-Experts for Biomedical Question Answering
inferredcites →https://doi.org/10.1007/978-3-642-00958-7openalex-snapshot
Advances in information retrieval : 31th European Conference on IR Research, ECIR 2009, Toulouse, France, April 6-9, 2009 : proceedings
inferredcites →https://doi.org/10.1007/b116168openalex-snapshot
Advances in Information Retrieval: Recent Research from the Center for Intelligent Information Retrieval
inferredcites →https://doi.org/10.1007/s10462-012-9338-yopenalex-snapshot
Mixture of experts: a literature survey
inferredcites →https://doi.org/10.1007/s10791-022-09411-0openalex-snapshot
Shallow pooling for sparse labels
inferredcites →https://doi.org/10.1016/0306-4573(94)00047-7openalex-snapshot
Overview of the Second Text Retrieval Conference (TREC-2)
inferredcites →https://doi.org/10.1016/0888-613x(87)90012-0openalex-snapshot
Architecture of an expert system for composite document analysis, representation, and retrieval
inferredcites →https://doi.org/10.1016/s0306-4573(00)00016-9openalex-snapshot
A probabilistic model of information retrieval: development and comparative experiments
inferredcites →https://doi.org/10.1038/238109a0openalex-snapshot
General: Effectiveness of Combining Title Words and Index Terms in Machine Retrieval Searches
inferredcites →https://doi.org/10.1109/tnnls.2012.2200299openalex-snapshot
Twenty Years of Mixture of Experts
inferredcites →https://doi.org/10.1109/tpami.2010.57openalex-snapshot
Product Quantization for Nearest Neighbor Search
inferredcites →https://doi.org/10.1142/9789812797926_0003openalex-snapshot
SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORK
inferredcites →https://doi.org/10.1145/1852102.1852106openalex-snapshot
A similarity measure for indefinite rankings
inferredcites →https://doi.org/10.1145/2983323.2983769openalex-snapshot
A Deep Relevance Matching Model for Ad-hoc Retrieval
inferredcites →https://doi.org/10.1145/3041021.3054192openalex-snapshot
Model Ensemble for Click Prediction in Bing Search Ads
inferredcites →https://doi.org/10.1145/3130348.3130368openalex-snapshot
A Language Modeling Approach to Information Retrieval
inferredcites →https://doi.org/10.1145/3298689.3346997openalex-snapshot
Recommending what video to watch next
inferredcites →https://doi.org/10.1145/3366423.3380258openalex-snapshot
Context-Aware Document Term Weighting for Ad-Hoc Search
inferredcites →https://doi.org/10.1145/3404835.3463098openalex-snapshot
SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
inferredcites →https://doi.org/10.1145/3404835.3463249openalex-snapshot
TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime
inferredcites →https://doi.org/10.1145/3477495.3531942openalex-snapshot
Automatic Expert Selection for Multi-Scenario and Multi-Task Search
inferredcites →https://doi.org/10.1145/3486250openalex-snapshot
Semantic Models for the First-Stage Retrieval: A Comprehensive Review
inferredcites →https://doi.org/10.1145/3511808.3557343openalex-snapshot
Hard Negatives or False Negatives
inferredcites →https://doi.org/10.1145/3580305.3599927openalex-snapshot
UnifieR: A Unified Retriever for Large-Scale Retrieval
inferredcites →https://doi.org/10.1145/3637870openalex-snapshot
Dense Text Retrieval Based on Pretrained Language Models: A Survey
inferredcites →https://doi.org/10.1162/neco.1991.3.1.79openalex-snapshot
Adaptive Mixtures of Local Experts
inferredcites →https://doi.org/10.1162/tacl_a_00276openalex-snapshot
Natural Questions: A Benchmark for Question Answering Research
inferredcites →https://doi.org/10.1162/tacl_a_00369openalex-snapshot
Sparse, Dense, and Attentional Representations for Text Retrieval
inferredcites →https://doi.org/10.1561/1500000019openalex-snapshot
The Probabilistic Relevance Framework: BM25 and Beyond
inferredcites →https://doi.org/10.1561/1500000100openalex-snapshot
Pre-training Methods in Information Retrieval
inferredcites →https://doi.org/10.1609/aaai.v34i05.6428openalex-snapshot
ERNIE 2.0: A Continual Pre-Training Framework for Language Understanding
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.550openalex-snapshot
Dense Passage Retrieval for Open-Domain Question Answering
inferredcites →https://doi.org/10.18653/v1/2021.emnlp-main.224openalex-snapshot
RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking
inferredcites →https://doi.org/10.18653/v1/2021.naacl-main.241openalex-snapshot
COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List
inferredcites →https://doi.org/10.18653/v1/2022.acl-long.203openalex-snapshot
Unsupervised Corpus Aware Language Model Pre-training for Dense Passage Retrieval
inferredcites →https://doi.org/10.18653/v1/2022.findings-emnlp.19openalex-snapshot
Salient Phrase Aware Dense Retrieval: Can a Dense Retriever Imitate a Sparse One?
inferredcites →https://doi.org/10.18653/v1/2024.findings-acl.137openalex-snapshot
M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation
inferredcites →https://doi.org/10.18653/v1/n19-1423openalex-snapshot
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
inferredcites →https://doi.org/10.48550/arxiv.2010.06467openalex-snapshot
Pretrained Transformers for Text Ranking: BERT and Beyond
inferredcites →https://doi.org/10.48550/arxiv.2304.03158openalex-snapshot
CoT-MAE v2: Contextual Masked Auto-Encoder with Multi-view Modeling for Passage Retrieval

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-36984-0_1openalex-snapshot
SIGNET: Motion-Level Knowledge Transfer for Cross-Language Sign Language Translation
inferred← citeshttps://doi.org/10.1007/s10844-026-01080-5openalex-snapshot
RCT-MARS: when per-query retrieval routing fails, and what it takes to succeed
inferred← citeshttps://doi.org/10.1016/b978-0-443-33362-0.00010-2openalex-snapshot
Cost efficient mixture of experts
inferred← citeshttps://doi.org/10.1109/asp-dac66049.2026.11420804openalex-snapshot
SpANNS: Optimizing Approximate Nearest Neighbor Search for Sparse Vectors Using Near Memory Processing
inferred← citeshttps://doi.org/10.1109/icde65448.2025.00333openalex-snapshot
M 2 oERank: Multi-Objective Mixture-of-Experts Enhanced Ranking for Satisfaction-Oriented Web Search
inferred← citeshttps://doi.org/10.1109/smc58881.2025.11342524openalex-snapshot
A Loss Weighting Algorithm Based on In-batch Positive Passage Rankings for Dense Retrievers
inferred← citeshttps://doi.org/10.1109/wimob66857.2025.11257454openalex-snapshot
Expert Fusion with Meta-Adaptation for Signal Technology Recognition
inferred← citeshttps://doi.org/10.1145/3709134openalex-snapshot
Pre-Trained Models for Search and Recommendation: Introduction to the Special Issue—Part 1
inferred← citeshttps://doi.org/10.20944/preprints202408.0583.v1openalex-snapshot
The Evolution of Mixture of Experts: A Survey from Basics to Breakthroughs
inferred← citeshttps://doi.org/10.20944/preprints202408.0583.v2openalex-snapshot
The Evolution of Mixture of Experts: A Survey from Basics to Breakthroughs
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