The paper proposes PrefixMem, a dedicated encoder for Semantic IDs (SIDs), demonstrating that structured, prefix-conditioned representations significantly improve the accuracy and recall of generative…

This paper proposes ChronoID, a framework for time-aware semantic ID learning in generative recommendation.

Taiji is a novel LLM-as-Enhancer framework that optimizes recommender systems by addressing the challenges of generating high-quality reasoning data and balancing semantic and ID-based rewards.

The paper proposes a comprehensive, dual-layer architectural framework for AI identification and traceability, ensuring continuous accountability and regulatory oversight throughout the entire lifecyc…

The paper introduces ANCHOR, a schema-agnostic system that constructs knowledge graphs from Cyber Threat Intelligence by dynamically discovering and validating against large ontologies, overcoming lim…

The paper introduces a semantic validation framework that uses unpackers as executable contracts to detect and repair semantic bugs in packer identification tools, significantly improving the reliabil…

The paper presents BEATS, a human-in-the-loop LLM framework for bootstrapping product attribute taxonomies from scratch.

The paper defines AI Identity as the correspondence between an agent's declared state and its observed behavior, concluding that current infrastructure and standards are fundamentally inadequate for g…

The paper introduces presidio-hardened-x402, an open-source middleware that intercepts x402 payment requests to detect and redact PII and enforce spending policies before on-chain settlement.

The paper introduces a novel semantic fingerprinting approach using Semantic Correlation Descriptors (SCDs) to identify which specific datasets were used to train a model, demonstrating superior perfo…

EviLink addresses the ambiguity of schema linking in Text-to-SQL by treating it as an uncertainty-aware inference over multiple plausible SQL paths, significantly improving recall and efficiency.

SS-ZKR is a novel, three-mechanism protocol that enables privacy-preserving, content-based semantic routing of agent payloads across organizational trust boundaries without requiring the intermediary…

SS-ZKR is a novel, three-mechanism protocol that enables privacy-preserving, content-based semantic routing of agent payloads across organizational trust boundaries without requiring the intermediary…

The paper proposes a Semantic Gateway and a Zero-Trust security model to formally validate and secure autonomous AI agents operating in enterprise systems, achieving a 100% discovery rate of unauthori…

The paper introduces PSR extsuperscript{2}, a novel static analysis framework that significantly improves the detection of atomicity violations in smart contracts by combining structural path searchin…

The paper introduces Compositional Semantic Fingerprinting (CSF), a black-box method that allows IP owners to attribute fine-tuned text-to-image models to their protected lineages using only query acc…

The paper proposes AgentDID, a decentralized framework using DIDs and verifiable credentials to provide trustless identity authentication and dynamic state verification for autonomous, self-managed AI…

The study compares agentic data retrieval using unstructured web data versus structured, semantically-annotated datasets, concluding that semantic metadata remains essential for high-precision, reliab…

The paper proposes a portable authorization standard for autonomous agents, addressing the structural gaps in existing identity models when agents operate across organizational boundaries.

SWAN introduces a novel, training-free framework that embeds watermarks directly into the semantic structure of a sentence using Abstract Meaning Representation (AMR), achieving superior robustness ag…