1180777 results (page 88 of 47232)
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Evaluation of Winning Solutions of 2025 Low Power Computer Vision Challenge
The IEEE Low-Power Computer Vision Challenge (LPCVC) aims to promote the development of efficient vision models for edge devices, balancing accuracy with constraints such as latency, memory capacity, and energy use. The 2025 challenge featured three tracks: (1) Image classification under various lighting conditions and styles, (2) Open-Vocabulary Segmentation with Text Prompt, and (3) Monocular De…
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CHRONOS: A Hardware-Assisted Phase-Decoupled Framework for Secure Federated Learning in IoT
We propose CHRONOS, a hardware-assisted framework that decouples the cryptographic setup required for private gradient aggregation from the active training phase. CHRONOS executes a once-per-epoch server-relayed Diffie-Hellman key exchange during a device's idle window. It generates ephemeral keypairs and derives PRG keys entirely within an ARM TrustZone enclave, ensuring private keys never exist …
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Cell-Based Representation of Relational Binding in Language Models
Understanding a discourse requires tracking entities and the relations that hold between them. While Large Language Models (LLMs) perform well on relational reasoning, the mechanism by which they bind entities, relations, and attributes remains unclear. We study discourse-level relational binding and show that LLMs encode it via a Cell-based Binding Representation (CBR): a low-dimensional linear s…
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Three-dimensional recoil-electron reconstruction using combined optical imaging and waveform readout for electron-tracking Compton cameras
Accurate reconstruction of recoil-electron directions is critical for enhancing the point-spread function of electron-tracking Compton cameras (ETCCs) in gamma-ray imaging. Although full three-dimensional (3D) readout systems achieve high-precision reconstruction, they are impractical for large-area detectors because of the enormous data volume. This study proposes and demonstrates a practical alt…
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Refute-or-Promote: An Adversarial Stage-Gated Multi-Agent Review Methodology for High-Precision LLM-Assisted Defect Discovery
LLM-assisted defect discovery has a precision crisis: plausible-but-wrong reports overwhelm maintainers and degrade credibility for real findings. We present Refute-or-Promote, an inference-time reliability pattern combining Stratified Context Hunting (SCH) for candidate generation, adversarial kill mandates, context asymmetry, and a Cross-Model Critic (CMC). Adversarial agents attempt to disprove…
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SAMoRA: Semantic-Aware Mixture of LoRA Experts for Task-Adaptive Learning
The combination of Mixture-of-Experts (MoE) and Low-Rank Adaptation (LoRA) has shown significant potential for enhancing the multi-task learning capabilities of Large Language Models. However, existing methods face two primary challenges: (1)Imprecise Routing in the current MoE-LoRA method fails to explicitly match input semantics with expert capabilities, leading to weak expert specialization. (2…
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RARE: Redundancy-Aware Retrieval Evaluation Framework for High-Similarity Corpora
Existing QA benchmarks typically assume distinct documents with minimal overlap, yet real-world retrieval-augmented generation (RAG) systems operate on corpora such as financial reports, legal codes, and patents, where information is highly redundant and documents exhibit strong inter-document similarity. This mismatch undermines evaluation validity: retrievers can be unfairly undervalued even whe…
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Learning Lifted Action Models from Unsupervised Visual Traces
Efficient construction of models capturing the preconditions and effects of actions is essential for applying AI planning in real-world domains. Extensive prior work has explored learning such models from high-level descriptions of state and/or action sequences. In this paper, we tackle a more challenging setting: learning lifted action models from sequences of state images, without action observa…
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STK-Adapter: Incorporating Evolving Graph and Event Chain for Temporal Knowledge Graph Extrapolation
Temporal Knowledge Graph (TKG) extrapolation aims to predict future events based on historical facts. Recent studies have attempted to enhance TKG extrapolation by integrating TKG's evolving structural representations and textual event chains into Large Language Models (LLMs). Yet, two main challenges limit these approaches: (1) The loss of essential spatial-temporal information due to shallow ali…
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Integrated Sensing and Communications for Low-Altitude Economy with Deterministic Sensing and Gaussian Information Signals
Reliable surveillance and communication for unmanned aerial vehicles (UAVs) are crucial for enabling and sustaining the accelerated growth of the low-altitude economy. Integrated sensing and communications (ISAC) offers a cost-effective and scalable framework for target sensing by leveraging existing wireless communication systems. This paper investigates a bistatic downlink ISAC architecture tail…
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Generative Texture Filtering
We present a generative method for texture filtering, which exhibits surprisingly good performance and generalizability. Our core idea is to empower texture filtering by taking full advantage of the strong learned image prior of pre-trained generative models. To this end, we propose to fine-tune a pre-trained generative model via a two-stage strategy. Specifically, we first conduct supervised fine…
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Explicit Factorization of $x^{p+1}-1$ over $\mathbb{Z}_{p^e}$: A Structural Approach via Dickson Polynomials
Let $p$ be an odd prime. The factorization of the polynomial $x^{p+1}-1$ over the integer residue ring $\mathbb{Z}_{p^e}$ is pivotal for constructing cyclic codes with Hermitian symmetry, a critical resource for Linear Complementary Dual (LCD) codes and Entanglement-Assisted Quantum Error-Correcting Codes (EAQECC). Traditionally, lifting factorizations relies on the generic Hensel's Lemma, masking…
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Plausible Reasoning and First-Order Plausible Logic
Defeasible statements are statements that are likely, or probable, or usually true, but may occasionally be false. Plausible reasoning makes conclusions from statements that are either facts or defeasible statements without using numbers. So there are no probabilities or suchlike involved. Seventeen principles of logics that do plausible reasoning are suggested and several important plausible reas…
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LLM-Viterbi: Semantic-Aware Decoding for Convolutional Codes
Traditional wireless communications rely solely on bit-level channel coding for error correction, without exploiting the inherent linguistic structure of the data source. This paper proposes a large language model (LLM) Viterbi decoder that integrates LLM priors into the Viterbi decoding for text transmission over AWGN channels. The proposed decoder maintains multiple candidate paths during the Vi…
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Explore Like Humans: Autonomous Exploration with Online SG-Memo Construction for Embodied Agents
Constructing structured spatial memory is essential for enabling long-horizon reasoning in complex embodied navigation tasks. Current memory construction predominantly relies on a decoupled, two-stage paradigm: agents first aggregate environmental data through exploration, followed by the offline reconstruction of spatial memory. However, this post-hoc and geometry-centric approach precludes agent…
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Intentional Updates for Streaming Reinforcement Learning
In gradient-based learning, a step size chosen in parameter units does not produce a predictable per-step change in function output. This often leads to instability in the streaming setting (i.e., batch size=1), where stochasticity is not averaged out and update magnitudes can momentarily become arbitrarily big or small. Instead, we propose intentional updates: first specify the intended outcome o…
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Analysis of AWW (Anganwadi Workers) Training Content, ILA (Incremental Learning Approach) Modules Following CDT (Component Display Theory)
POSHAN Abhiyan envisages capacity building of AWWs or frontline health workers through 21 training modules of ILA (Incremental Learning Approach), modularising the net learning content into smaller learning topics to help them perform their daily activities. It envisions building skilled AWWs, strengthening supervisory hierarchies, and improving coordination between AWWs (ICDS) services and health…
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SAGE: Signal-Amplified Guided Embeddings for LLM-based Vulnerability Detection
Software vulnerabilities are a primary threat to modern infrastructure. While static analysis and Graph Neural Networks have long served as the foundation for vulnerability detection, the emergence of Large Language Models (LLMs) has introduced a transformative paradigm driven by superior semantic reasoning and cross-environment generalization. However, in the context of LLM-based vulnerability de…
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Geometric quantification for nonlinear deformation in knitted fabrics
Knitted fabrics exemplify a broad class of architected materials capable of large deformations, enabling shape morphing, mechanical biocompatibility, and embedded multifunctionality without material damage. Although geometric nonlinearity has been intuitively utilized in their design, a quantitative description of stitch-resolved deformation and its temporal evolution remains lacking. Here, we int…
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Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors
One of the most challenging problems in graph machine learning is generalizing across graphs with diverse properties. Graph neural networks (GNNs) face a fundamental limitation: they require separate training for each new graph, preventing universal generalization across diverse graph datasets. A critical challenge facing GNNs lies in their reliance on labeled training data for each individual gra…
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Neural Operator Representation of Granular Micromechanics-based Failure Envelope
Micromechanics-based granular models are widely used to predict the failure behavior of porous and particulate materials, including concrete, soils, foams, and biological tissues. Although these models offer considerable flexibility through microstructural parametrization and statistical representation, their mapping to macroscopic responses, particularly failure envelopes, is implicit and require…
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ClawCoin: An Agentic AI-Native Cryptocurrency for Decentralized Agent Economies
Autonomous AI agents live or die by the API tokens they consume: without paid inference capacity they cannot reason, act, or delegate. Compute-token cost has become the binding resource of the emerging agent economy, yet it is non-transferable: it is account-bound, vendor-specific, and absent from on-chain ledgers. Existing payment rails such as x402 move fiat-backed value between agents, but they…
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RoomRecon: High-Quality Textured Room Layout Reconstruction on Mobile Devices
Widespread RGB-Depth (RGB-D) sensors and advanced 3D reconstruction technologies facilitate the capture of indoor spaces, improving the fields of augmented reality (AR), virtual reality (VR), and extended reality (XR). Nevertheless, current technologies still face limitations, such as the inability to reflect minor scene changes without a complete recapture, the lack of semantic scene understandin…
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Policy Gradient Primal-Dual Method for Safe Reinforcement Learning from Human Feedback
Safe Reinforcement Learning from Human Feedback (Safe RLHF) has recently achieved empirical success in developing helpful and harmless large language models by decoupling human preferences regarding helpfulness and harmlessness. Existing approaches typically rely on fitting fixed horizon reward models from human feedback and have only been validated empirically. In this paper, we formulate safe RL…
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Seeing at Timau National Observatory Based on ERA5 Dataset
Understanding the seeing conditions is crucial for astronomical observations using a ground-based telescope. This study analyzes long-term atmospheric data (2002-2021) from the ERA5 dataset to assess the seeing conditions at the new Timau National Observatory in Indonesia, which will house a 3.8-meter optical telescope. While the ERA5 dataset shows good agreement with radiosonde data for temperatu…