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Deep learning for anomaly detection: A review
Anomaly detection, aka outlier detection or novelty detection, has been a lasting yet active
research area in various research communities for several decades. There are still some …
research area in various research communities for several decades. There are still some …
Fair ranking: a critical review, challenges, and future directions
Ranking, recommendation, and retrieval systems are widely used in online platforms and
other societal systems, including e-commerce, media-streaming, admissions, gig platforms …
other societal systems, including e-commerce, media-streaming, admissions, gig platforms …
Judging llm-as-a-judge with mt-bench and chatbot arena
L Zheng, WL Chiang, Y Sheng… - Advances in …, 2023 - proceedings.neurips.cc
Evaluating large language model (LLM) based chat assistants is challenging due to their
broad capabilities and the inadequacy of existing benchmarks in measuring human …
broad capabilities and the inadequacy of existing benchmarks in measuring human …
Bias and debias in recommender system: A survey and future directions
While recent years have witnessed a rapid growth of research papers on recommender
system (RS), most of the papers focus on inventing machine learning models to better fit …
system (RS), most of the papers focus on inventing machine learning models to better fit …
Mllm-as-a-judge: Assessing multimodal llm-as-a-judge with vision-language benchmark
Multimodal Large Language Models (MLLMs) have gained significant attention recently,
showing remarkable potential in artificial general intelligence. However, assessing the utility …
showing remarkable potential in artificial general intelligence. However, assessing the utility …
Judgelm: Fine-tuned large language models are scalable judges
Evaluating Large Language Models (LLMs) in open-ended scenarios is challenging
because existing benchmarks and metrics can not measure them comprehensively. To …
because existing benchmarks and metrics can not measure them comprehensively. To …
Socially responsible ai algorithms: Issues, purposes, and challenges
In the current era, people and society have grown increasingly reliant on artificial
intelligence (AI) technologies. AI has the potential to drive us towards a future in which all of …
intelligence (AI) technologies. AI has the potential to drive us towards a future in which all of …
Causerec: Counterfactual user sequence synthesis for sequential recommendation
Learning user representations based on historical behaviors lies at the core of modern
recommender systems. Recent advances in sequential recommenders have convincingly …
recommender systems. Recent advances in sequential recommenders have convincingly …
Measuring misinformation in video search platforms: An audit study on YouTube
Search engines are the primary gateways of information. Yet, they do not take into account
the credibility of search results. There is a growing concern that YouTube, the second largest …
the credibility of search results. There is a growing concern that YouTube, the second largest …
Controlling fairness and bias in dynamic learning-to-rank
Rankings are the primary interface through which many online platforms match users to
items (eg news, products, music, video). In these two-sided markets, not only the users draw …
items (eg news, products, music, video). In these two-sided markets, not only the users draw …