SQuAD2.0
PulseAugur coverage of SQuAD2.0 — every cluster mentioning SQuAD2.0 across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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New research probes LLMs' ability to detect unanswerable questions
Researchers have developed a method to detect when large language models (LLMs) are answering questions they cannot truly answer, or responding prematurely in a dialogue. They created a new benchmark and evaluation harn…
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New research tackles LLM quantization robustness and uncertainty preservation
Two new research papers explore methods to improve the quantization of large language models (LLMs) while preserving their performance and uncertainty behavior. The first paper, "Jacobian-guided Noise Injection for Quan…
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New framework optimizes LLM use for extractive question answering
Researchers have developed a Learning-to-Defer framework to improve the efficiency of extractive question answering (EQA) using large language models. This method intelligently allocates queries to specialized models, e…