Topic - Edition
How a decision-first model can catch risky tool calls before they turn into real-world actions The post Can TypeSafe's Jev Make AI Agents Safer Without Another LLM? appeared first on Towards Data Science.
The cost of control The post Where Does the Money Go Across Long-Running Coding Agents? appeared first on Towards Data Science.
AI Agents for Beginners, Part 1 The post Build Your First AI Agent with One Tool Call appeared first on Towards Data Science.
AI agents can now write more code than any of us can read. That changed how I think about AI. The post Stop Using AI. Start Hiring It. appeared first on Towards Data Science.
Microsoft Research engineer Alex Lavaee explains how to verify AI-written code using Atomic, independent reviewers, real-world tests, and reproducible evidence.
Anthropic’s new policy prohibits extreme, purposeless abuse toward Claude. The restriction brings AI welfare into product rules while researchers continue to investigate whether chatbots can suffer.
arXiv:2610.12167v1 Announce Type: new Abstract: Generalist graph anomaly detection (GAD) aims to build a foundation model that detects anomalies on arbitrary unseen graphs without retraining or fine-tuning. Sufficient…
arXiv:2610.10615v1 Announce Type: cross Abstract: Choosing which information to observe is central to prediction under limited observation budgets. We study JevForest, a feature acquisition policy that aggregates…
arXiv:2610.11382v1 Announce Type: cross Abstract: World models in end-to-end autonomous driving predict future scene evolution to provide foresight for trajectory planning. Existing methods mainly study how to predict…
arXiv:2610.03827v2 Announce Type: replace-cross Abstract: Similarity scores are often offered as evidence that a model shares structure with the brain or across languages. We ask what such a score reads when that…
arXiv:2610.10623v1 Announce Type: new Abstract: Looped Language Models (LoopLMs) offer a parameter efficient approach to scaling reasoning by reusing shared parameters across recurrent computation steps. Despite their…
arXiv:2610.11222v1 Announce Type: cross Abstract: Preclinical models poorly predict human drug efficacy, particularly in neurological disorders. Neural activity offers a uniquely rich source of translational information…
arXiv:2608.19584v3 Announce Type: replace Abstract: We study landscapes for complex-parameterized networks. Our approach is motivated with an information-theoretic manifold perspective of the parameter and via classical…
arXiv:2605.10414v2 Announce Type: replace Abstract: Rotary Positional Encoding (RoPE) is widely used in modern large language models. However, when sequences are extended beyond the range seen during training, rotary…
arXiv:2610.11196v1 Announce Type: cross Abstract: Large audio-language models (LALMs) exploit multimodal evidence, yet task-irrelevant audio can alter text-reasoning decisions when listening is unnecessary. Aggregate…
arXiv:2610.11730v1 Announce Type: new Abstract: Standard weight decay treats each weight matrix as a vector and ignores its spectral structure. We introduce spectral weight decay, a post-step decoupled nuclear-norm…
arXiv:2610.11748v1 Announce Type: cross Abstract: U-Net inference for brain-tumor segmentation requires billions of multiply-accumulate operations, motivating hardware that can reduce computation dynamically rather than…
arXiv:2610.11201v1 Announce Type: cross Abstract: Dynamic sparse attention limits the KV pages selected by each query, but a small support does not necessarily yield efficient GPU work. Query unions share page loads and…
arXiv:2610.11914v1 Announce Type: new Abstract: High-resolution socioeconomic variables are important for applications such as urban planning, public health, disaster response, and resource allocation. In practice,…
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