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
David Cota’s evaluation of the author’s “participatory explanation” approach to consciousness reveals fundamental conceptual problems that plague contemporary consciousness studies. Cota identifies a critical conflation between reason as a symbolic-operational function, and consciousness as a phenomenal-experiential fi...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
David Cota’s evaluation of the author’s “participatory explanation” approach to consciousness reveals fundamental conceptual problems that plague contemporary consciousness studies. Cota identifies a critical conflation between reason as a symbolic-operational function, and consciousness as a phenomenal-experiential fi...
Kwan Hong TAN· Zenodo (CERN European Organi...· 0 citations
This work introduces Schur Replay, a scale-selection algorithm that reproduces the GPTQ updates caused by each block scale and scores the resulting block error after accounting for compensation from unquantized columns.
Rui-Ying Ding, Jie Li, Kang He et al.· 0 citations
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Fisher-IRG yields stronger semantic-versus-nuisance predictive selectivity and generally more reproducible subspaces than covariance-based geometry, while recovering systematically distinct local directions.
This work introduces Video2Skill, a benchmark that covers robot tabletop manipulation and human kitchen activity and tests three core capabilities: locating manipulation events in time, grouping events of the same transformation, and deciding when to reuse an existing skill or create a new one.
Jian-Shu Zhang, Ce Zhang, Xi-Yuan Yang et al.· 0 citations
A holistic framework based on learnable information gain, which measures how much novel, parameterizable information a round provides relative to the previous round, and proposes ATRI (Adaptive Training Regulation via Information-gain), which reweights samples within a round and halts training across rounds when inform...
Chen-Xu Wang, Chao-Zhuo Li, Xin-Ze Shi et al.· 0 citations
CaRE-KD is proposed, a confidence-gated distillation framework that replaces static objectives with uncertainty-adaptive optimization and provides a gradient-level analysis showing how this dual-granularity design induces a conditional calibration mechanism that prior static divergences cannot reproduce.
Experimental results show that AMU maintains cleaner and more retrievable personalized memories, and an SLM-guided (Small language model guided) structured framework for writing-time memory control.
This work learns a shared semantic frame and sparse coordinates that reconstruct semantic displacements while suppressing nuisance variation, with anchor-dependent diagonal modulation adjusting atom strengths without sample-specific rotations to support reusable invariant directions as a sparse coordinate system for lo...
Group Relative Policy Optimization (GRPO) is widely used to train reasoning language models, where it computes advantages by centering and normalizing rewards across rollouts of the same prompt. For multiple rewards, GRPO sums the reward components and normalizes the total reward by its within-group standard deviation....
Wen-Bin Hu, Hui-Hao Jing, Hao-Chen Shi et al.· 0 citations
Many of the qualities that matter most in how people learn and grow, how someone regulates their emotions, reflects on a setback, or stays aware of others during a difficult conversation, are not directly observable. They have to be inferred from how someone speaks, moves, and sounds over time, and they resist the kind...
Siddhant Jain, Dimitra Tsovaltzi· Companion Publication of the...· 0 citations
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.eduSep 24, 2026
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.
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