From matching to generation: A survey on generative information retrieval
Information Retrieval (IR) systems are crucial tools for users to access information, widely
applied in scenarios like search engines, question answering, and recommendation …
applied in scenarios like search engines, question answering, and recommendation …
Aligning llm agents by learning latent preference from user edits
We study interactive learning of language agents based on user edits made to the agent's
output. In a typical setting such as writing assistants, the user interacts with a language …
output. In a typical setting such as writing assistants, the user interacts with a language …
From persona to personalization: A survey on role-playing language agents
Recent advancements in large language models (LLMs) have significantly boosted the rise
of Role-Playing Language Agents (RPLAs), ie, specialized AI systems designed to simulate …
of Role-Playing Language Agents (RPLAs), ie, specialized AI systems designed to simulate …
Optimization methods for personalizing large language models through retrieval augmentation
This paper studies retrieval-augmented approaches for personalizing large language
models (LLMs), which potentially have a substantial impact on various applications and …
models (LLMs), which potentially have a substantial impact on various applications and …
Social skill training with large language models
People rely on social skills like conflict resolution to communicate effectively and to thrive in
both work and personal life. However, practice environments for social skills are typically out …
both work and personal life. However, practice environments for social skills are typically out …
Hydra: Model factorization framework for black-box llm personalization
Personalization has emerged as a critical research area in modern intelligent systems,
focusing on mining users' behavioral history and adapting to their preferences for delivering …
focusing on mining users' behavioral history and adapting to their preferences for delivering …
Democratizing large language models via personalized parameter-efficient fine-tuning
Personalization in large language models (LLMs) is increasingly important, aiming to align
the LLMs' interactions, content, and recommendations with individual user preferences …
the LLMs' interactions, content, and recommendations with individual user preferences …
Review of the opportunities and challenges to accelerate mass‐scale application of smart grids with large‐language models
Smart grids represent a paradigm shift in the electricity industry, moving from traditional one‐
way systems to more dynamic, interconnected networks. These grids are characterised by …
way systems to more dynamic, interconnected networks. These grids are characterised by …
Comparing retrieval-augmentation and parameter-efficient fine-tuning for privacy-preserving personalization of large language models
Privacy-preserving methods for personalizing large language models (LLMs) are relatively
under-explored. There are two schools of thought on this topic:(1) generating personalized …
under-explored. There are two schools of thought on this topic:(1) generating personalized …
Longlamp: A benchmark for personalized long-form text generation
I Kumar, S Viswanathan, S Yerra, A Salemi… - arxiv preprint arxiv …, 2024 - arxiv.org
Long-text generation is seemingly ubiquitous in real-world applications of large language
models such as generating an email or writing a review. Despite the fundamental …
models such as generating an email or writing a review. Despite the fundamental …