New research shows AI language models mirror how the human brain builds meaning over time while listening to natural speech.
AI models including GPT-4.1 and DeepSeek-3.1 can mirror ingroup versus outgroup bias in everyday language, a study finds. Researchers also report an ION training method that reduced the gap.
When models are trained on unverified AI slop, results drift from reality fast. Here's how to stop the spread, according to Gartner.
transformers had made a major change on kv cache implementation since version 4.36.0. Please use ppl_legacy if you are using transformers < 4.36.0 ...
Every time we speak, we're improvising. "Humans possess a remarkable ability to talk about almost anything, sometimes putting ...
Yann LeCun is a Turing Award recipient and a top AI researcher, but he has long been a contrarian figure in the tech world.
We propose TraceRL, a trajectory-aware reinforcement learning method for diffusion language models, which demonstrates the best performance among RL approaches for DLMs. We also introduce a ...
Abstract: This paper presents a novel method for generating realistic stimuli for dynamic power estimation in video coding transform hardware. Our proposal is based on Markov chains and its goal is to ...
Abstract: Parkinson's disease (PD) is frequently accompanied by motor symptoms such as tremor and bradykinesia, as well as non-motor symptoms, including cognitive impairment. It has been indicated ...
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