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Mathematical reasoning remains underexplored for low-resource languages, including Dialectal Arabic. To bridge this gap, we introduce the DAR-MGSM (Dialectal Arabic Multilingual Grade School Math) Benchmark, the first ma...
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Modern distributed microservice deployments generate massive volumes of heterogeneous, multi-format observability logs across physically and logically partitioned infrastructure. Isolating root causes during cascading fa...
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Picture-description dementia classification uses a shared visual scene, but a transcript-level prediction alone does not identify the scene evidence underlying its inputs. NarraSpace links words and speech times to named...
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Multi-token prediction (MTP) can accelerate language-model decoding by drafting several tokens and verifying them in a single target-model pass. However, the best speculation horizon changes with context: longer drafts o...
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Planning under uncertain control execution noise requires reliable feedback policies across diverse environments. We introduce Planning Under Noise (PUN), a neural operator that learns noise-aware value fields for planni...
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Motivated by the human ability to integrate experience across language, perception, and action, we introduce UniWALM, a unified world-action-language model that learns video, action, and language in a single shared repre...
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Dexterous multi-finger hands hold promise to unlock diverse skills like functional grasps, in-hand reorientation, and dynamic handover that the human-designed world assumes, yet existing learning recipes force a trade-of...
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The development of face recognition has been strongly supported by the availability of large-scale training datasets. Among them, MS-Celeb-1M has played an important role by providing millions of facial images from nearl...
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Non-uniform allocation can improve post-training pruning of large language models, yet quality can still degrade sharply at high sparsity. To control degradation as sparsity increases, we introduce LADDER (Layer-Wise All...
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Iterative ML agents develop models by editing code, running experiments, reading a validation score, and choosing what to try next. In current harnesses this loop is served by an exact validation score returned after eve...
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We revisit the problem of depth separation for neural networks, as studied by Eldan and Shamir, Daniely, and others. Specifically, we consider the natural setting of $L^2$ approximation of radial functions under the stan...
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Community Choice Aggregators (CCAs) play an important role in the energy transition by procuring renewable electricity for local communities while balancing affordability, resource adequacy, and clean-energy requirements...
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Constrained-random verification tests hardware designs by sampling solutions of Boolean formulas. Existing samplers largely follow one of two approaches: CPU-based SAT samplers (e.g., CMSGen), which remain effective even...
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This paper investigates a multi-objective optimiza tion framework for UAV-mounted reconfigurable intelligent sur face (STAR-RIS)-assisted Sixth Generation (6G)-enabled Internet of Things (IoT) systems. The considered fra...
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The widespread adoption of generative artificial intelligence in recent years has brought a parallel rise in prompt injection and jailbreak attacks. By embedding malicious instructions, these exploits manipulate language...