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ai Sep 16 When Should LLMs Abstain? Chain-of-Self-Questioning for Selective Risk Control LLMs Should Know When to Say "I Don't Know" Language models are fluent by default. Ask them a question they cannot answer, and they will produce something that sounds right, reads well, and might be completely wrong. In healthcare... ai Sep 16 Verifiable Social Reasoning for LLM Assistants Why Your Chatbot Can't Read Between the Lines When you tell your LLM assistant that a coworker seems a little too eager to help, you're giving it a subjective, filtered, emotionally loaded account of reality. The assistant never s... ai Sep 16 LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence A Tabular Foundation Model That Learns Joint Distributions, Not Just Predictions Tabular data is the unglamorous backbone of machine learning in practice. Healthcare records, financial transactions, sensor readings, scientific mea... ai Sep 16 JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management Fitting a 27B-Parameter LLM into 24 GiB of Laptop Memory The promise of local LLM inference is straightforward: run capable models on hardware you own, keep your data private, and avoid API costs. The obstacle is equally straightf... ai Sep 16 World Model Science: Self-Organized Criticality, Weak Chaos, and Metastable Belief Dynamics in Long-Horizon LLM Agents When an LLM agent runs a long task, it accumulates state: progress markers, beliefs, constraints, uncertainties, tool debt, and intermediate plans. Standard evaluation asks one question: did the final answer pass? This paper asks... machine learning Sep 16 Knowledge as Orbit: Finite Collections as Phases of an Exactly Periodic Latent Generator Machine learning stores knowledge extensionally. Every item in a collection gets its own code, its own latent vector, its own row in a codebook. For X objects, you need X entries. The question this paper asks is whether a finite c... ai Sep 15 Show HN: Sunk Cost – How long until a local LLM rig pays for itself? A new web tool called Sunk Cost attempts to answer a question every developer running local language models eventually asks: how many API calls does it take before the GPU you already bought starts saving you money? The calculator... programming languages Sep 14 SNAP3D: Physically Grounded 3D Parts for Assembly from a Single Image Part-aware 3D generation has advanced rapidly, but there is a disconnect between producing individual parts that look right and producing parts that actually hold together as a physical assembly. A chair rendered as separate legs,... machine learning Sep 14 Type Diversity Enables Transformers to Generalise Compositionally The compositional generalisation problem has haunted Transformer research for years. Train a seq2seq model on "John drinks coffee" and it learns to translate that just fine. But give it "John drinks coffee on a mat" when only "on... ai Sep 14 From Review to Reuse: How Post-Task Workflow Can Support Human-AI Agent Interaction When you ask an AI agent to complete a multi-step task, you hand over a single natural-language prompt and get back a result. Everything that happens in between, the tool calls, the file manipulations, the branching logic, the err...