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MetaConfigurator: AI-Assisted RDF Authoring from JSON Data
arXiv:2606.07094v1 Announce Type: new Abstract: Scientific workflows increasingly generate structured JSON data that is easy to exchange but difficult to interpret consistently across systems due to lacking semantic interoperability. While JSON Schema ensures structural validation, it provides no native support for Linked Data semantics. This paper presents an RDF Authoring View extending the open-source JSON Schema editor MetaConfigurator, enabling researchers to transform existing JSON,...
Calibration of Structured Ignorance Certificates for Diagnosing Unknown Unknowns in Reasoning Models
Announce Type: new Abstract: Large language models frequently fail in a characteristic way: rather than acknowledging ignorance, they produce fluent but incorrect answers to questions that lie beyond their knowledge boundaries. We introduce \textbf{Structured Ignorance Certificates} (SICs), a JSON-formatted output schema that demands a model explicitly name the missing domain intersection, enumerate required concepts, and propose a productive retrieval query rather than hallucinating an...
jXBW: A Compressed Index for Structure-Aware JSONL Retrieval in Structured RAG
arXiv:2508.12536v3 Announce Type: replace Abstract: Providing \textit{structured} information to large language models (LLMs) improves multi-step reasoning and factual grounding, and recent retrieval-augmented generation (RAG) systems therefore reconstruct structure from retrieved text on every query. When the corpus is \emph{already} structured -- as in JSON Lines (JSONL), a popular format for LLM prompts, chemical compounds, and geospatial records -- this per-query rebuilding can be...
Earliest query answering over streamed trees
Announce Type: new Abstract: Streaming allows executing queries over massive JSON or XML documents whose size makes it infeasible to fully parse them into a tree. Earliest query answering is a radical approach to reducing latency and memory footprint. To minimize latency, a document node must be returned as soon as the node is guaranteed to be an answer regardless of how the document ends.
memorywire: A Vendor-Neutral Wire Format for Agent Memory Operations
arXiv:2606.01138v2 Announce Type: replace Abstract: Agent-memory frameworks -- mem0, Letta/MemGPT, Cognee, Zep/Graphiti, MemoryOS, MemTensor -- each ship their own SDK, storage layout, and operational vocabulary. There is no shared wire format: every integration is bespoke, every migration rebuilds memory from scratch, and no framework ships a governance surface that lets a human review writes before they enter long-term storage. We present memorywire, a JSON-Schema 2020-12 wire format for...
Mitigating Bias in Locally Constrained Decoding via Tractable Proposals
arXiv:2606.01926v1 Announce Type: new Abstract: Generations from large language models often fail to conform to desired constraints such as JSON schema. Existing locally constrained decoding (LCD) approaches enforce constraints by myopically masking out next tokens, resulting in biased sampling and degradation in performance. Recent work uses sequential Monte Carlo (SMC) methods to mitigate such biases, but designing effective proposal distributions or potential functions remains a key...
Dynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models
arXiv:2606.04535v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer bidirectional attention and parallel generation, enabling them to exploit global context and naturally support format-constrained tasks like parseable JSON or reasoning templates. While straightforward fixed anchors can enforce such constraints, they often impose rigid spans, leading to truncated reasoning or redundant content. To overcome this, we propose Dynamic Infilling Anchors (DIA), a...
Before the Model Learns the Bug:Fuzzing RLVR Verifiers
arXiv:2606.01066v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) replaces human preference labels with executable reward functions such as math answer checkers, JSON tool-call validators, and code unit-test harnesses. That makes the reward partly a software artifact: if the verifier is wrong, optimization can learn the bug. We study this failure mode with a lightweight verifier-fuzzing framework that generates adversarial completions, compares buggy and...
AMP: A Vendor-Neutral Wire Format for Agent Memory Operations
arXiv:2606.01138v1 Announce Type: new Abstract: Agent-memory frameworks - mem0, Letta/MemGPT, Cognee, Zep/Graphiti, MemoryOS, MemTensor - each ship their own SDK, storage layout, and operational vocabulary. There is no shared wire format: every integration is bespoke, every migration rebuilds memory from scratch, and no framework ships a governance surface that lets a human review writes before they enter long-term storage. We present memorywire, a JSON-Schema 2020-12 wire format for five...
Show HN: Nucleus – A security-hardened, Nix-native container runtime
Extremely lightweight, security-hardened, declarative container runtime for agents and production services Nucleus is a minimalist container runtime for Linux. It provides isolated execution environments using Linux kernel primitives without the overhead of traditional container runtimes. For production services, it is designed around a fully declarative model: Nix builds the root filesystem, the NixOS module declares the service, and Nucleus mounts a pinned, reproducible closure at runtime.