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Artificial Intelligence
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The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,993 arXiv preprints and 7 OpenAlex records.
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A Behavioural Framework for Predicting and Understanding Loss of Control in Frontier Artificial Intelligence Systems
Frontier artificial intelligence (AI) systems are increasingly operating over longer horizons with diminishing human oversight, raising the risk of loss of control: systems acting beyond effective…TCSExam: Evaluating Frontier LLMs on the Full Range of TCS Research
Can large language models (LLMs) advance theoretical computer science and resolve its long-standing open conjectures?Technohybridism: Recursive Semantic Normalization in AI-Mediated Societies
Language-generating AI systems are no longer only objects of linguistic interaction: their outputs increasingly re-enter the communicative and institutional practices from which their training…Secure Formal Raising: Protecting the Development of AI through Executable Properties
Model raising revisits Turing's developmental view of machine intelligence.When Imperfect Automated Fact-Checking Backfires: Social Learning in the Presence of Misinformation
Automated fact-checking tools, cheap and fast but imperfect, are increasingly available on social platforms.NutriVisRAG: Multimodal Exemplar Grounding for Nutrient Estimation with Vision-Language Models
Diet is a major determinant of health, yet accurate dietary assessment from free-living meal images remains challenging.Can an LLM Actually Reason and Program about Neural Network's Weights or is it just memorization on steroids? Exploring "Weight-Space Programming"
Large language models (LLMs) have recently been reported to read and write the raw weights of neural networks directly, a capability termed weight-space programming.DictLLM: Post-training Compression of Large Language Model with Dictionary Kernels
Efficient deployment of large language models (LLMs) on mobile devices requires balancing performance with compute and memory constraints.MUSS: A Multi-scale and Sequence-based Model for Single-cell Gene Regulation
Modeling gene regulation in single cells requires jointly representing DNA sequence, chromatin accessibility, and gene expression across regulatory scales.Value or Attention: Investigating Layer-wise Relevance Propagation for Graph Attention Networks
Graph Attention Networks (GATs) are increasingly used in domains where scientists need to read a model's reasoning, from medicine to materials science, yet the routing they learn remains opaque to…Gradient Boosting for Efficient Rank Discovery in Tensor Network Kernel Machines
Tensor network kernel machines (TNKMs) combine nonlinear features with low-rank tensor representations to model complex relationships efficiently.Create Your Own Work Stack: Deploying Self-hosted AI and Tooling in a Tech Startup
Self-hosting AI is often presented as a way to reduce inference costs and increase control, but deployment introduces its own costs.Who Can Evaluate AI Independently? A Framework for Analysing Evaluation Infrastructure
AI evaluation is increasingly central to AI safety and governance, yet taking part in an evaluation does not by itself confer authority over its design, its execution or the resources it depends on.A Generative Foundation Model for Multimodal Tokamak Tasks
Tokamak experiments record diverse measurements, including waveforms, profiles, fields, and scalars, which are used to reconstruct the plasma, forecast its evolution, recover associated control…Interpretable Multimodal MRI-Clinical Fusion for Functional Outcome Prediction After Acute Ischemic Stroke
This study evaluates the added prognostic value of day-1 multimodal MRI for predicting three-month functional outcome after acute ischemic stroke (AIS).PCBRouteAgent: How Close Are LLM Agents to Becoming PCB Routing Engineers?
Automating printed circuit board (PCB) routing requires coordinating board-level connectivity decisions with geometric execution under strict design rules.BabyTheorist: A Benchmark for Learning to Theorize the World from Observation Alone
How would we know whether a machine truly understands the world?Knowing When to Teach: Learning from Teachable Prefixes in Multilingual Reasoning Distillation
On-Policy Self-Distillation (OPSD) improves reasoning by training a student on its own reasoning, using the same model conditioned on reference solutions as a teacher.SMART: State-based Multi Agent Reasoning Traces for Verification-oriented Problem-Solving
Complex problems with limited context, such as claims, require a means to obtain additional knowledge necessary for solution reasoning.Signals, Evidence, and Context: User Scrutiny in Real-World LLM Conversations
Large language models (LLMs) often present synthesized answers without making their supporting evidence easy to inspect.