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20242026
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cs.CL2025

DynaSaur: Large Language Agents Beyond Predefined Actions

Dang Nguyen, Viet Dac Lai, Seunghyun Yoon +9

Existing LLM agent systems typically select actions from a fixed and predefined set at every step. While this approach is effective in closed, narrowly scoped environments, it pres…

cs.CL2025

Personalization of Large Language Models: A Survey

Zhehao Zhang, Ryan A. Rossi, Branislav Kveton +18

Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications. Despite the importance and recent progress, most exist…

cs.CL2025

Personalized Graph-Based Retrieval for Large Language Models

Steven Au, Cameron J. Dimacali, Ojasmitha Pedirappagari +7

As large language models (LLMs) evolve, their ability to deliver personalized and context-aware responses offers transformative potential for improving user experiences. Existing p…

cs.CL2025

A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations

Li Li, Peilin Cai, Ryan A. Rossi +21

We present PersonaConvBench, a large-scale benchmark for evaluating personalized reasoning and generation in multi-turn conversations with large language models (LLMs). Unlike exis…

cs.CL2024

GRS-QA -- Graph Reasoning-Structured Question Answering Dataset

Anish Pahilajani, Devasha Trivedi, Jincen Shuai +7

Large Language Models (LLMs) have excelled in multi-hop question-answering (M-QA) due to their advanced reasoning abilities. However, the impact of the inherent reasoning structure…

cs.CL2024

A Survey of Small Language Models

Chien Van Nguyen, Xuan Shen, Ryan Aponte +25

Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, maki…