This paper introduces a novel methodology, the Knowledge Graph Large Language Model Framework (KG-LLM), which leverages pivotal NLP paradigms, including chain-of-thought (CoT) prompting and in-context learning (ICL), to enhance multi-hop link prediction in KGs. By converting the KG to a CoT ...
It should be noted that the use of social robots in special education is not the focus of this work; it is a subject that has been extensively researched in the literature, and as such, does not need to be systematically reviewed again in the context of this paper. Yet, it is useful ...
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In this paper, we aim to systematically investigate the capabilities of GPT-4o in addressing 10 low-level data analysis tasks. Our study seeks to answer the following critical questions, shedding light on the potential of MLLMs in performing detailed, granular analyses. ...
We show that chain-of-thought prompting, which was used to increase accuracy, may also provide insight into the model’s reasoning or trajectory. It is possible that the LLM is imitating plausible reasoning rather than providing insight into how it actually arrived at its answer; however, this...
The answer to these questions lies in scaling laws. Scaling laws determines how much optimal data is required to train a model of a particular size. In 2022, DeepMind proposed the scaling laws for training the LLMs with the optimal model size and dataset (no. of tokens) in the paperTraini...
Paper Link: ([2410.18032] GraphTeam: Facilitating Large Language Model-based Graph Analysis via Multi-Agent Collaboration) Contents Introduction System Requirements Installation Steps 1. Create a Conda Virtual Environment 2. Install Dependencies 3. Using Docker Running the Project 1. Activate the Cond...
This paper provides a survey of the emerging area of Large Language Models (LLMs) for Software Engineering (SE). It also sets out open research challenges for the application of LLMs to technical problems faced by software engineers. LLMs' emergent properties bring novelty and creativity with ...
Besides Q2, and Q7, Supplementary Table S8-S9 indicates that the baseline model also had very poor Accuracymentioned on SDoH questions Q3 (Does the patient currently use tobacco?) and Q5 (Does the patient currently use illicit drugs?). This is likely attributable to the fact that the ...
Moreover, we also developed computational analyses that build on psychological models such as the similarity-coverage model. All of the analyses in this paper are thus examples of LLM cognitive psychology. However, future work could draw on ideas from other branches of psychology. For example, ...