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Found 6 papers, 1 papers with code
SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactions
Natural language interaction with sensing systems is crucial for enabling all users to comprehend sensor data and its impact on their everyday lives.
SensorQA: A Question Answering Benchmark for Daily-Life Monitoring
To address this gap, we introduce SensorQA, the first human-created question-answering (QA) dataset for long-term time-series sensor data for daily life monitoring.
"Yeah Right!" -- Do LLMs Exhibit Multimodal Feature Transfer?
In this paper, we assess the ability of speech+text models and text models trained with special emphasis on human-to-human conversations to make this multimodal transfer of skill.
Reading with Intent -- Neutralizing Intent
The context for retrieval-augmented generation (RAG) systems in most benchmarks comes from Wikipedia or Wikipedia-like texts which are written in a neutral and factual tone.
Reading with Intent
Retrieval augmented generation (RAG) systems augment how knowledge language models are by integrating external information sources such as Wikipedia, internal documents, scientific papers, or the open internet.
Dense Passage Retrieval: Is it Retrieving?
We also uncover a limitation in this training style: the internal knowledge of the pre-trained model bounds what the retrieval model can retrieve.
