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41 papers · 1 filter
Lizard: An Efficient Linearization Framework for Large Language Models
Chien Van Nguyen, Huy Nguyen, Ruiyi Zhang +10
We propose Lizard, a linearization framework that transforms pretrained Transformer-based Large Language Models (LLMs) into subquadratic architectures. Transformers faces severe co…
ScreenLLM: Stateful Screen Schema for Efficient Action Understanding and Prediction
Yiqiao Jin, Stefano Petrangeli, Yu Shen +1
Graphical User Interface (GUI) agents are autonomous systems that interpret and generate actions, enabling intelligent user assistance and automation. Effective training of these a…
A Framework for Fine-Tuning LLMs using Heterogeneous Feedback
Ryan Aponte, Ryan A. Rossi, Shunan Guo +5
Large language models (LLMs) have been applied to a wide range of tasks, including text summarization, web navigation, and chatbots. They have benefitted from supervised fine-tunin…
Improving the Capabilities of Large Language Model Based Marketing Analytics Copilots With Semantic Search And Fine-Tuning
Yilin Gao, Sai Kumar Arava, Yancheng Li +1
Artificial intelligence (AI) is widely deployed to solve problems related to marketing attribution and budget optimization. However, AI models can be quite complex, and it can be d…
Contextual Multilingual Spellchecker for User Queries
Sanat Sharma, Josep Valls-Vargas, Tracy Holloway King +2
Spellchecking is one of the most fundamental and widely used search features. Correcting incorrectly spelled user queries not only enhances the user experience but is expected by t…
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling
Yuchen Zhuang, Yue Yu, Lingkai Kong +2
Learning from noisy labels is a challenge that arises in many real-world applications where training data can contain incorrect or corrupted labels. When fine-tuning language model…