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arXiv:2603.03080v1 Announce Type: new Abstract: LLM-based explainable recommenders can produce fluent explanations that are factually correct, yet still justify items using attributes that conflict with …
arXiv:2603.03097v1 Announce Type: new Abstract: We present Odin, the first production-deployed graph intelligence engine for autonomous discovery of meaningful patterns in knowledge graphs without prior …
arXiv:2603.03116v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents are increasingly adopted in high-stakes settings, but current benchmarks evaluate mainly whether a task was …
arXiv:2603.03119v1 Announce Type: new Abstract: Agentic AI deployments increasingly behave as persistent institutions rather than one-shot inference endpoints: they accumulate state, invoke external tools, coordinate …
arXiv:2603.03147v1 Announce Type: new Abstract: Coverage closure is a critical requirement in Integrated Chip (IC) development process and key metric for verification sign-off. However, traditional …
arXiv:2603.03175v1 Announce Type: new Abstract: Saarthi is an agentic AI framework that uses multi-agent collaboration to perform end-to-end formal verification. Even though the framework provides …
arXiv:2603.03176v1 Announce Type: new Abstract: Hierarchical text classification (HTC) and extreme multi-label classification (XML) tasks face compounded challenges from complex label interdependencies, data sparsity, and …
arXiv:2603.03177v1 Announce Type: new Abstract: The integration of symbolic computing with neural networks has intrigued researchers since the first theorizations of Artificial intelligence (AI). The …
arXiv:2603.03190v1 Announce Type: new Abstract: During music listening, cortical activity encodes both acoustic and expectation-related information. Prior work has shown that ANN representations resemble cortical …
arXiv:2603.03203v1 Announce Type: new Abstract: CDD, or Contamination Detection via output Distribution, identifies data contamination by measuring the peakedness of a model's sampled outputs. We …
arXiv:2603.03212v1 Announce Type: new Abstract: Real-time proactive agentic system, capable of modeling Human State of Mind, using foundation EXG model and text embeddings model, running …
arXiv:2603.03233v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate potentials for automating scientific code generation but face challenges in reliability, error propagation in multi-agent …