From the 1 of 10 linked papers with an AI index.
10 papers
Know It, Act on It: Investigating Memory Utilization in LLM Personalization
Zhaoxin Feng, Jianfei Ma, Emmanuele Chersoni
As large language model (LLM) agents evolve into personalized companions, memory has emerged as a core capability. However, LLMs face a knowledge utilization problem: they may fail…
Every Time I Hire a Linguist, Inference Costs Go Down: On Linguistic Rules as Effective Prompt Compressors
Jianfei Ma, Zhaoxin Feng, Emmanuele Chersoni +1
The paper explores using deterministic linguistic rules as prompt compressors to shorten inputs for large language models, eliminating the need for costly model-based token scoring…
Is Length Really A Liability? An Evaluation of Multi-turn LLM Conversations using BoolQ
Karl Neergaard, Le Qiu, Emmanuele Chersoni
Single-prompt evaluations dominate current LLM benchmarking, yet they fail to capture the conversational dynamics where real-world harm occurs. In this study, we examined whether c…
Can Large Language Models Understand, Reason About, and Generate Code-Switched Text?
Genta Indra Winata, David Anugraha, Patrick Amadeus Irawan +15
Code-switching is a pervasive phenomenon in multilingual communication, yet the robustness of large language models (LLMs) in mixed-language settings remains insufficiently underst…
From BERT to LLMs: Comparing and Understanding Chinese Classifier Prediction in Language Models
Ziqi Zhang, Jianfei Ma, Emmanuele Chersoni +2
Classifiers are an important and defining feature of the Chinese language, and their correct prediction is key to numerous educational applications. Yet, whether the most popular L…
Learning to Look at the Other Side: A Semantic Probing Study of Word Embeddings in LLMs with Enabled Bidirectional Attention
Zhaoxin Feng, Jianfei Ma, Emmanuele Chersoni +2
Autoregressive Large Language Models (LLMs) demonstrate exceptional performance in language understanding and generation. However, their application in text embedding tasks has bee…