Papers › LaMP: When Large Language Models Meet Personalization

LaMP: When Large Language Models Meet Personalization

22 Apr 2023arXiv:2304.11406archive 2025-07-28

Alireza Salemi, Sheshera Mysore, Michael Bendersky, Hamed Zamani

This paper highlights the importance of personalization in large language models and introduces the LaMP benchmark -- a novel benchmark for training and evaluating language models for producing personalized outputs. LaMP offers a comprehensive evaluation framework with diverse language tasks and multiple entries for each user profile. It consists of seven personalized tasks, spanning three text classification and four text generation tasks. We additionally propose two retrieval augmentation approaches that retrieve personal items from each user profile for personalizing language model outputs. To this aim, we study various retrieval models, including term matching, semantic matching, and time-aware methods. Extensive experiments on LaMP for zero-shot and fine-tuned language models demonstrate the efficacy of the proposed retrieval augmentation approach and highlight the impact of personalization in various natural language tasks.

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Bingo-W/Personalisation-in-LLM mentioned on GitHubpytorchMIT report
TamSiuhin/Per-Pcs mentioned on GitHubpytorch report
lamp-benchmark/lamp mentioned on GitHubpytorch report
tamsiuhin/oppu mentioned on GitHubpytorch report

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1ran · our draft was wrong
12unverified

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add_double_quote Bingo-W/Personalisation-in-LLM/data_process/lamp_prompt.py community (archive-listed) unverified MIT (permissive) · b853890170bdd63b · report
bm25_for_LaMP_1 Bingo-W/Personalisation-in-LLM/retrival_models/bm25.py community (archive-listed) unverified MIT (permissive) · 23f0b1f0e49789e5 · report
bm25_for_LaMP_2 Bingo-W/Personalisation-in-LLM/retrival_models/bm25.py community (archive-listed) unverified MIT (permissive) · ea15f50f0290cb27 · report
bm25_for_LaMP_2_old Bingo-W/Personalisation-in-LLM/retrival_models/bm25.py community (archive-listed) unverified MIT (permissive) · e8b485a887f3a97c · report
build_random_fn Bingo-W/Personalisation-in-LLM/retrival_models/random_selection.py community (archive-listed) unverified MIT (permissive) · 24c2f3f44b2eb90f · report
construct_for_llama2 Bingo-W/Personalisation-in-LLM/data_process/utils.py community (archive-listed) unverified MIT (permissive) · e0c399c2fee303db · report
contact Bingo-W/Personalisation-in-LLM/data_process/lamp_prompt.py community (archive-listed) unverified MIT (permissive) · 3904f6728f0da676 · report
extract_quote Bingo-W/Personalisation-in-LLM/retrival_models/utils.py community (archive-listed) unverified MIT (permissive) · 4d32a60c24f98603 · report
list_merge Bingo-W/Personalisation-in-LLM/data_process/utils.py community (archive-listed) unverified MIT (permissive) · 6e3557815a51535b · report
merge_user_profile Bingo-W/Personalisation-in-LLM/data_process/utils.py community (archive-listed) unverified MIT (permissive) · 0d2320ebef045b45 · report
random_in_user Bingo-W/Personalisation-in-LLM/retrival_models/random_selection.py community (archive-listed) unverified MIT (permissive) · a92fdabe69c67804 · report
reorder_list_middle Bingo-W/Personalisation-in-LLM/data_process/lamp_prompt.py community (archive-listed) unverified MIT (permissive) · e26359c5ce67f9d1 · report
mean_pooling identical code first harvested elsewhere ran · our draft was wrong fingerprinted licence of this copy not recorded · fe0e2df4d9cb5edd · report

Tasks

Language ModelingLanguage ModellingNatural Language UnderstandingRetrievalText ClassificationText Generationtext-classification

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