The question of whether algorithms can be considered epistemic agents represents one of the most profound challenges at the intersection of philosophy of mind, epistemology, and artificial intelligence. This paper develops a novel theoretical framework for understanding algorithmic epistemic agency through the introduc...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
The question of whether moral facts are real or constructed has dominated metaethical discourse for centuries, with traditional positions including moral realism, anti-realism, and constructivism offering competing accounts of moral ontology. This paper introduces four novel theoretical frameworks that transcend tradit...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
The question of whether moral facts are real or constructed has dominated metaethical discourse for centuries, with traditional positions including moral realism, anti-realism, and constructivism offering competing accounts of moral ontology. This paper introduces four novel theoretical frameworks that transcend tradit...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Proposals that physical states and laws jointly determine one another are often presented through fixed-point equations. Yet any ordinary fixed-law theory can be rewritten in joint fixed-point form by adding a constant law-update map. Fixed-point form alone therefore carries neither empirical content nor a distinctive...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
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Proposals that physical states and laws jointly determine one another are often presented through fixed-point equations. Yet any ordinary fixed-law theory can be rewritten in joint fixed-point form by adding a constant law-update map. Fixed-point form alone therefore carries neither empirical content nor a distinctive...
Kwan Hong TAN· PhilPapers (PhilPapers Found...· 0 citations
This article develops a joint state-law fixed-point method for self-consistent quantum models. A physical model is represented by a density operator and a finite-dimensional vector of effective law parameters; admissible dynamics consist of a state-update channel and a law-update map. A recursive solution is their join...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
This article develops a joint state-law fixed-point method for self-consistent quantum models. A physical model is represented by a density operator and a finite-dimensional vector of effective law parameters; admissible dynamics consist of a state-update channel and a law-update map. A recursive solution is their join...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
Deep reinforcement learning for quantum circuit optimization faces three bottlenecks: replay buffers that overlook temporal difference (TD) target reliability, curriculum-based architecture search requiring a full quantum-classical evaluation after every edit, and the discard of noiseless trajectories when retraining u...
Frozen language models (LMs) are increasingly used as fixed feature extractors for downstream reranking, scoring, and preference modeling, raising a practical question: how should a compact module represent interactions among features in a fixed low-dimensional bottleneck? Common linear and low-rank adapters remain lin...
E. Roh, Hyojun Ahn, Hoyeong Lee et al.· 0 citations
A minimal single-qubit reservoir reproduces the HHG response of a substantially larger Ising spin chain, and on a representative benchmark matches and on several metrics surpasses previously reported temporal convolutional and Kolmogorov--Arnold-network models, while using a simpler, physically realizable system.
Abhijit Sen, B. Parida, Shital Chauhan et al.· 0 citations
Evaluating near-term quantum-kernel support vector machines on practical network-security classification tasks and using quantum oracle sketching (QOS) to study a longer-term memory advantage for classification with streaming classical samples shows how quantum computing may contribute to network-security classificatio...
This work leverages Stein's lemma and Lipschitz concentration bounds for Gaussian random variables to provide an analytical lower bound of the variance of the gradient and a probabilistic concentration bound of the deviation of the gradient from its mean.
Gennaro De Luca, Vinayak Sharma, Aviral Shrivastava· arXiv.org· 2 citations
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
Microsoft Research Blog· microsoft.comOct 21, 2026
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
