MIT News July 31, 2024 Recent studies have found that common interventions such as instruction tuning often result in poorly calibrated large language models (LLMs). Although calibration is well-explored in traditional applications, calibrating LLMs is uniquely challenging. The challenges stem as much from the severe computational requirements of LLMs as from their versatility, which allows them to be applied to diverse tasks. To address these challenges, researchers at MIT proposed THERMOMETER, a calibration approach tailored to LLMs. For calibrating the LLMTHERMOMETER learned an auxiliary model, using the data given from multiple tasks. According to the researchers it was computationally efficient, […]
Tag Archives: AI models
AI models struggle to identify nonsense, says study
Phys.org September 14, 2023 Neural network language models appear to be increasingly aligned with how humans process and generate language, but identifying their weaknesses through adversarial examples is challenging due to the discrete nature of language and the complexity of human language perception. An international team of researchers (USA – Columbia University, Israel) turned the models against each other by generating controversial sentence pairs where two language models disagreed about which sentence is more likely to occur. Considering nine language models (including n-gram, recurrent neural networks, and transformers), they created hundreds of controversial sentence pairs through synthetic optimization or by […]