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7 papers · 1 filter
Learning and Enforcing Context-Sensitive Control for LLMs
Mohammad Albinhassan, Pranava Madhyastha, Mark Law +1
Controlling the output of Large Language Models (LLMs) through context-sensitive constraints has emerged as a promising approach to overcome the limitations of Context-Free Grammar…
Retrieval-augmented reasoning with lean language models
Ryan Sze-Yin Chan, Federico Nanni, Tomas Lazauskas +6
This technical report details a novel approach to combining reasoning and retrieval augmented generation (RAG) within a single, lean language model architecture. While existing RAG…
Evaluating the Ability of Large Language Models to Reason about Cardinal Directions
Anthony G Cohn, Robert E Blackwell
We investigate the abilities of a representative set of Large language Models (LLMs) to reason about cardinal directions (CDs). To do so, we create two datasets: the first, co-crea…
How Can We Effectively Expand the Vocabulary of LLMs with 0.01GB of Target Language Text?
Atsuki Yamaguchi, Aline Villavicencio, Nikolaos Aletras
Large language models (LLMs) have shown remarkable capabilities in many languages beyond English. Yet, LLMs require more inference steps when generating non-English text due to the…
Emotion fusion for mental illness detection from social media: A survey
Tianlin Zhang, Kailai Yang, Shaoxiong Ji +1
Mental illnesses are one of the most prevalent public health problems worldwide, which negatively influence people's lives and society's health. With the increasing popularity of s…
Rationalizing Predictions by Adversarial Information Calibration
Lei Sha, Oana-Maria Camburu, Thomas Lukasiewicz
Explaining the predictions of AI models is paramount in safety-critical applications, such as in legal or medical domains. One form of explanation for a prediction is an extractive…