The prevalence of misinformation on social media threatens public trust, demanding automated fact-checking systems that provide accurate verdicts with interpretable explanations. However, existing large language model-based (LLM-based) approaches often rely heavily on external knowledge sources, introducing substantial latency and even hallucinations that undermine reliability, interpretability, and responsiveness, which is crucial for real-time use. To address these challenges, we propose REason-guided Fact-checking with Latent EXplanations REFLEX paradigm, a plug-and-play, self-refining paradigm that leverages the internal knowledge in backbone model to improve both verdict accuracy and explanation quality. REFLEX reformulates fact-checking as a role-play dialogue and jointly trains verdict prediction and explanation generation. It adaptively extracts contrastive activation pairs between the backbone model and its fine-tuned variant to construct steering vectors that disentangle truth into style and substance naturally. These activation-level signals guide inference and suppress noisy explanations, enabling more faithful and efficient reasoning. Experiments on real-world datasets show that REFLEX outperforms previous methods that steer toward a single truth direction and underscores the challenge traditional approaches face when handling the subtle, human-unknown truth in fact-checking tasks. Remarkably, with only 465 self-refined training samples, RELFEX achieves state-of-the-art performance. Furthermore, models trained with explanatory objectives can effectively guide those without them, yielding up to a 7.57% improvement, highlighting that internal explanation signals play a dual role in both interpreting and enhancing factual reasoning.

Evaluating log summarization systems is challenging due to the lack of high-quality reference summaries and the limitations of existing metrics like ROUGE and BLEU, which depend on surface-level lexical overlap. We introduce REFLEX, a reference-free evaluation metric for log summarization based on large language model (LLM) judgment. REFLEX uses LLMs as zero-shot evaluators to assess summary quality along dimensions such as relevance, informativeness, and coherence, without requiring gold-standard references or human annotations. We show that REFLEX produces stable, interpretable, and fine-grained evaluations across multiple log summarization dataset, and more effectively distinguishes model outputs than traditional metrics. REFLEX provides a scalable alternative for evaluating log summaries in real-world settings where reference data is scarce or unavailable.

You might spend top dollar for fancy new graphics card hardware, but one of the key components to gaming performance is actually software. While the brute force of the hardware gets most of the glory (and is indeed essential), the software side is the magic that pieces it together. Without good software, even the ferocious Nvidia GeForce RTX 4090 is reduced to a fancy paperweight--especially when running Cyberpunk 2077's glorious new path traced Overdrive mode. Software can also substantially improve the hardware performance. Including both AI-powered frame generation and Nvidia's wondrous latency-reducing Reflex technology, DLSS 3.0 makes for a potent recipe. And with the unveiling of affordable new GeForce RTX 4060 and 4060 Ti graphics cards, this fantastic technology is about to become a lot more accessible. This isn't the same old DLSS upsampling you're used to, however.

You might spend top dollar for fancy new graphics card hardware, but one of the key components to gaming performance is actually software. While the brute force of the hardware gets most of the glory (and is indeed essential), the software side is the magic that pieces it together. Without good software, even the ferocious Nvidia GeForce RTX 4090 is reduced to a fancy paperweight--especially when running Cyberpunk 2077's glorious new path traced Overdrive mode. Software can also substantially improve the hardware performance. Including both AI-powered frame generation and Nvidia's wondrous latency-reducing Reflex technology, DLSS 3.0 makes for a potent recipe. This isn't the same old DLSS upsampling you're used to, however. We're going to go over some basics of what DLSS 3.0 is, and its application to Nvidia's RTX 40-series GPUs.

We develop a systems theoretical treatment of a behavioural system that interacts with its environment in a closed loop situation such that its mo- tor actions influence its sensor inputs. The simplest form of a feedback is a reflex. Reflexes occur always "too late"; i.e., only after a (unpleas- ant, painful, dangerous) reflex-eliciting sensor event has occurred. This defines an objective problem which can be solved if another sensor input exists which can predict the primary reflex and can generate an earlier reaction. In contrast to previous approaches, our linear learning algo- rithm allows for an analytical proof that this system learns to apply feed- forward control with the result that slow feedback loops are replaced by their equivalent feed-forward controller creating a forward model.

Cyberpunk 2077 has a lot to live up to. We called its grand E3 2018 reveal "the most mind-blowing demo we've ever seen." Witcher 3, CD Projekt Red's previous game, earned a prime spot as one of our favorite games of this generation. Witcher 3 actually usurped Deus Ex as my personal favorite game of all time, so CD Projekt Red working on a first-person cyberpunk role-playing game is as close to a "dream game" as I could envision. Add in Keanu Reeves and a star-studded custom soundtrack that includes a banger from Run The Jewels--my favorite musicians of this millennium--and this hype train couldn't possibly be more stoked.