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Semantic Audio-driven Understanding for Dynamic Humanoid Whole Body Control
This paper addresses the limitation in current humanoid robotic performances that rely heavily on pre-scripted sequences with limited autonomy and.

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This paper addresses the limitation in current humanoid robotic performances that rely heavily on pre-scripted sequences with limited autonomy and.

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This paper addresses the challenge of multi-task affective behavior analysis in-the-wild, specifically the ABAW11 Multi-Task Learning Challenge that.

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This paper presents iNORG, an open-source quantum impurity solver based on the Natural Orbitals Renormalization Group (NORG) method, designed to.

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This paper addresses the core challenge of credit assignment in long-horizon agentic reinforcement learning, where an agent must perform many sequential.

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VisualRepair addresses the challenge of automated program repair (APR) in modern software systems where bug reports contain heterogeneous and complex.

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This paper investigates how the adoption of automated bots as active participants influences the social organization and coordination capabilities of.

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xChk addresses a fundamental gap in identity provisioning for OAuth 2.0 / OpenID Connect ecosystems by enabling Bring Your Own Identity (BYOI) with.

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This paper addresses the key challenges in scaling quantum key distribution (QKD) networks across heterogeneous infrastructures and administrative.

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This systematic literature review (SLR) addresses the emerging interdisciplinary field combining Artificial Intelligence (AI) and Cyberpsychology (CPSY).

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Astra is an open-source, cross-platform Python software system designed to fully autonomously control robotic astronomical observatories without requiring.

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This paper proposes a novel approach to Full Disk Encryption (FDE) by interposing a general-purpose single-board computer (SBC) with USB On-The-Go support.

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This paper investigates the true extent of adoption and authenticity of the x402 agentic commerce protocol, which implements AI agents paying on-chain for.