Intentionqa: A benchmark for evaluating purchase intention comprehension abilities of language models in e-commerce
Enhancing Language Models'(LMs) ability to understand purchase intentions in E-
commerce scenarios is crucial for their effective assistance in various downstream tasks …
commerce scenarios is crucial for their effective assistance in various downstream tasks …
Miner: Mining the underlying pattern of modality-specific neurons in multimodal large language models
In recent years, multimodal large language models (MLLMs) have significantly advanced,
integrating more modalities into diverse applications. However, the lack of explainability …
integrating more modalities into diverse applications. However, the lack of explainability …
Errorradar: Benchmarking complex mathematical reasoning of multimodal large language models via error detection
As the field of Multimodal Large Language Models (MLLMs) continues to evolve, their
potential to revolutionize artificial intelligence is particularly promising, especially in …
potential to revolutionize artificial intelligence is particularly promising, especially in …
KnowComp at DialAM-2024: Fine-tuning Pre-trained Language Models for Dialogical Argument Mining with Inference Anchoring Theory
In this paper, we present our framework for DialAM-2024 TaskA: Identification of
Propositional Relations and TaskB: Identification of Illocutionary Relations. The goal of task …
Propositional Relations and TaskB: Identification of Illocutionary Relations. The goal of task …
Miko: Multimodal Intention Knowledge Distillation from Large Language Models for Social-Media Commonsense Discovery
Social media has become ubiquitous for connecting with others, staying updated with news,
expressing opinions, and finding entertainment. However, understanding the intention …
expressing opinions, and finding entertainment. However, understanding the intention …
EcomEdit: An Automated E-commerce Knowledge Editing Framework for Enhanced Product and Purchase Intention Understanding
Knowledge Editing (KE) aims to correct and update factual information in Large Language
Models (LLMs) to ensure accuracy and relevance without computationally expensive fine …
Models (LLMs) to ensure accuracy and relevance without computationally expensive fine …
[PDF][PDF] Benchmarking Large Language Models for E-commerce: Sentiment Analysis and Causal Inference in Customer Feedback
A Sadeed, A Anippe - researchgate.net
Abstract Benchmarking Large Language Models (LLMs) for e-commerce involves assessing
their performance in sentiment analysis and causal inference to enhance understanding of …
their performance in sentiment analysis and causal inference to enhance understanding of …