Instead of relying on the LLM itself to unlearn, we enforce an unlearned state during inference by employing a prompt classifier to identify and safeguard prompts to forget.

Reasoning over TKGs has two challenges: 1.

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Could Ukraine hold a presidential election right now? Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? 'Ukraine is running out of men, money and time' Ukrainian President Volodymyr Zelenskyy said that a state of emergency was being declared for Ukraine's energy sector, after repeated Russian attacks destroyed electricity and heat infrastructure. Zelenskyy said he asked the government to review curfew restrictions during "this extremely cold weather".

Developed by Texas A&M University engineering students, this AI-powered robotic dog doesn't just follow commands. Designed to navigate chaos with precision, the robot could help revolutionize search-and-rescue missions, disaster response and many other emergency operations. Sandun Vitharana, an engineering technology master's student, and Sanjaya Mallikarachchi, an interdisciplinary engineering doctoral student, spearheaded the invention of the robotic dog. It can process voice commands and uses AI and camera input to perform path planning and identify objects. A roboticist would describe it as a terrestrial robot that uses a memory-driven navigation system powered by a multimodal large language model (MLLM).

We show that for unconstrained Deep Linear Discriminant Analysis (LDA) classifiers, maximum-likelihood training admits pathological solutions in which class means drift together, covariances collapse, and the learned representation becomes almost non-discriminative. Conversely, cross-entropy training yields excellent accuracy but decouples the head from the underlying generative model, leading to highly inconsistent parameter estimates. To reconcile generative structure with discriminative performance, we introduce the \emph{Discriminative Negative Log-Likelihood} (DNLL) loss, which augments the LDA log-likelihood with a simple penalty on the mixture density. DNLL can be interpreted as standard LDA NLL plus a term that explicitly discourages regions where several classes are simultaneously likely. Deep LDA trained with DNLL produces clean, well-separated latent spaces, matches the test accuracy of softmax classifiers on synthetic data and standard image benchmarks, and yields substantially better calibrated predictive probabilities, restoring a coherent probabilistic interpretation to deep discriminant models.

Could Ukraine hold a presidential election right now? Will Europe use frozen Russian assets to fund war? How can Ukraine rebuild China ties? 'Ukraine is running out of men, money and time' An explosion in Moscow killed three people, including two police officers, just days after a car bomb killed a high-ranking Russian general in the same area of the capital. An official from Ukraine's military intelligence, known as GUR, told The Associated Press news agency that the attack had been carried out as part of a Ukrainian operation and the two police officers were targeted for taking part in Russia's war in Ukraine.