1 citations · 2 across the 13 of their papers we have counts for
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PediaMind-R1: A Temperament-Aware Language Model for Personalized Early Childhood Care Reasoning via Cognitive Modeling and Preference Alignment
Zihe Zhang, Can Zhang, Yanheng Xu +2
This paper presents PediaMind-R1, a domain-specialized large language model designed to achieve active personalization in intelligent parenting scenarios. Unlike conventional syste…
ScheduleMe: Multi-Agent Calendar Assistant
Oshadha Wijerathne, Amandi Nimasha, Dushan Fernando +2
Recent advancements in LLMs have contributed to the rise of advanced conversational assistants that can assist with user needs through natural language conversation. This paper pre…
Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models
Xinmiao Hu, Chun Wang, Ruihe An +4
Multimodal Large Language Models (MLLMs) have demonstrated strong performance in visual understanding tasks, yet they often suffer from object hallucinations--generating descriptio…
DebateBench: A Challenging Long Context Reasoning Benchmark For Large Language Models
Utkarsh Tiwari, Aryan Seth, Adi Mukherjee +3
We introduce DebateBench, a novel dataset consisting of an extensive collection of transcripts and metadata from some of the world's most prestigious competitive debates. The datas…
ARISE: Iterative Rule Induction and Synthetic Data Generation for Text Classification
Yashwanth M., Vaibhav Singh, Ayush Maheshwari +2
We propose ARISE, a framework that iteratively induces rules and generates synthetic data for text classification. We combine synthetic data generation and automatic rule induction…
Multi-branch of Attention Yields Accurate Results for Tabular Data
Xuechen Li, Yupeng Li, Jian Liu +2
Tabular data inherently exhibits significant feature heterogeneity, but existing transformer-based methods lack specialized mechanisms to handle this property. To bridge the gap, w…