Slator - Language Industry News

Joining SlatorPod this week is   Steven Piantadosi , Associate Professor of Psychology at UC Berkeley. Steven also runs   the computation and language lab   (colala) at UC Berkeley, which studies the basic computational processes involved in human language and cognition. Steven talks about the emergence of  large language models  ( LLMs ) and how it has reshaped our understanding of language processing and language acquisition. Steven breaks down his March 2023 paper, “ Modern language models refute Chomsky’s approach to language ”. He argues that LLMs demonstrate a wide range of powerful language abilities and disprove foundational assumptions underpinning Noam Chomsky’s theories and, as a consequence, negate parts of modern. Steven shares how he prompted  ChatGPT  to generate coherent and sensible responses that go beyond its training data, showcasing its ability to produce creative outputs. While critics argue that it is merely an endless sequence o...

  Large language models  (LLMs) have demonstrated   impressive machine translation (MT) capabilities , but new research shows they can generate different types of hallucinations compared to traditional models when deployed in real-world settings.  The findings, published in a  paper  on March 28, 2023, included evidence that the hallucinations were more prevalent when translating into low-resource languages and out of English and that they can introduce  toxic  text. Hallucinations present a critical challenge in MT, as they may damage user trust and pose serious safety concerns, according to a  2022 research paper , though studies to improve the detection and mitigation of hallucinations in MT have been limited to small models trained on a single English-centric language pair. This has left “a gap in our understanding of hallucinations […] across diverse translation scenarios,” explained Nuno M. Guerreiro and Duarte M. Alves from the  U...