arXiv:2602.00986v1 Announce Type: new Abstract: In this paper, we identify a sparse reward subsystem within the hidden states of Large Language Models (LLMs), drawing an analogy to the biological reward subsystem in the human brain. We demonstrate that this subsystem contains value neurons that represent the model’s internal expectation of state value, and through intervention experiments, we establish the importance of these neurons for reasoning. Our experiments reveal that these value neurons are robust across diverse datasets, model […]

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It’s also reasonable for people who entered technology in the last couple of decades because it was good job, or because they enjoyed coding to look at this moment with a real feeling of loss. That feeling of loss though can be hard to understand emotionally for people my age who entered tech because we were addicted to feeling of agency it gave us. The web was objectively awful as a technology, and genuinely amazing, and nobody got […]

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Apple announced the MacBook Neo two days ago. $599. iPhone chip. Four colors including “citrus” yellow. Ships March 11. I’m not an Apple user but I’ve been following rumors for a while. With the specs officially out, I have thoughts. Not all of them are positive. What it actually is MacBook Neo is the cheapest laptop Apple has ever sold. At $599 – or $499 if you’re a student – that’s great. What sucks: A18 Pro chip instead […]

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Author(s): Andrii Tkachuk Originally published on Towards AI. Over the past year, memory has become one of the most overused — and misunderstood — concepts in AI agent design. But before I start, I want to add a few words, most of us building AI agents today didn’t start as “AI engineers”. We come from backend engineering, data engineering, or data science. That background shapes how we think about systems: scalability, reliability, clear lifecycles, and predictable failure modes. […]

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If you follow the discourse surrounding AI security today, you’d be forgiven for thinking we’re standing on the edge of an existential cliff. The headlines and security warnings are relentless, painting a picture of an immediate and unprecedented threat landscape. Every week brings a new, dire headline that seems to amplify the sense of impending crisis: “AI agents can be tricked into attacking systems” This often refers to research demonstrating how autonomous AI systems, designed to perform helpful […]

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arXiv:2603.02250v1 Announce Type: new Abstract: Explaining the behavior of end-to-end audio language models via Shapley value attribution is intractable under native tokenization: a typical utterance yields over $150$ encoder frames, inflating the coalition space by roughly $10^{42}$ relative to text; individual audio frames lack standalone meaning; and token boundaries that bisect phonetic transitions introduce masking artifacts. We introduce Spectrogram-Guided Phonetic Alignment (SGPA), a four-stage pipeline that combines Connectionist Temporal Classification forced alignment with spectral boundary refinement to produce […]

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In this quiz, you’ll test your understanding of Tapping Into the Zen of Python. By working through this quiz, you’ll revisit the origins of the poem, the meaning of several aphorisms, and the inside jokes hidden throughout. The questions explore how the principles apply in practice and when it’s okay to bend the rules in the name of practicality. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to […]

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arXiv:2602.21221v1 Announce Type: new Abstract: Efficient long-context LLM deployment is stalled by a dichotomy between amortized compression, which struggles with out-of-distribution generalization, and Test-Time Training, which incurs prohibitive synthetic data costs and requires modifying model weights, creating stateful parameters that complicate concurrent serving. We propose Latent Context Compilation, a framework that fundamentally shifts context processing from adaptation to compilation. By utilizing a disposable LoRA module as a compiler, we distill long contexts into compact buffer tokens — stateless, […]

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arXiv:2603.25768v1 Announce Type: new Abstract: Functional verification remains a critical bottleneck in modern IC development cycles, accounting for approximately 70% of total development time in many projects. However, traditional methods, including constrained-random and formal verification, struggle to keep pace with the growing complexity of modern semiconductor designs. While recent advances in Large Language Models (LLMs) have shown promise in code generation and task automation, significant challenges hinder the realization of end-to-end functional verification automation. These challenges include (i) […]

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arXiv:2603.16875v1 Announce Type: new Abstract: Within the expansive domain of virtual reality (VR), 360{deg} VR videos immerse viewers in a spherical environment, allowing them to explore and interact with the virtual world from all angles. While this video representation offers unparalleled levels of immersion, it often lacks effective methods to guide viewers’ attention toward specific elements within the virtual environment. This paper combines the models Grounding Dino and Segment Anything (SAM) to guide attention by object focusing based […]

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