AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,629 papers
The constrained case of this"model size vs. inference compute"trade-off, in which the model outputs are constrained by a strict grammar at inference time, is examined, which demonstrates that the constrained trade-off behaves differently from the unconstrained trade-off.
RTLGuard leverages a teacher-student framework designed to sanitize compromised RTL generation models by fine-tuning a small-scale,"clean"teacher model on a limited set of trusted RTL data, and incorporating feature alignment and knowledge distillation to suppress malicious behaviors.
Spectral-Aware Muon is introduced, which holds the head at the Muon scale and amplifies the bulk using a static spectral prior, and both variants outperform tuned AdamW and Muon (Scion implementation) baselines in all evaluated model-scale and batch-size configurations.
This work proposes a label-free selection criterion built on SUDO, a framework for evaluating clinical AI systems without ground-truth annotations, and shows that AURCC can be used to rank a variety of vision-language models on chest X-ray classification across three inter-hospital shift scenarios, under zero-shot and...
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Linguistic meaning is grounded in conceptual content, from which reference to particular entities emerges as words enter discourse. To examine the processing dynamics associated with these two dimensions of meaning, we selectively disrupted conceptual or referential information in short narratives and traced the result...
MoganBert-TR, a 149M-parameter Turkish encoder foundation model trained from scratch on a language-specifically filtered corpus, together with an embedding model derived from it (MoganBert-Embed) that ranks first among student models on the MTEB(Turkish) overall average and outperforms all compared Turkish tokenizers o...
This paper introduces a programming language-agnostic, transferable, adversarial attack that exploits this CLM vulnerability and demonstrates that this attack, even when computed using smaller code embedding models, is highly effective and transferable to larger, closed-source embedding models.
This work presents a production retrieve-then-match cascade that spends computation in proportion to difficulty: retrieval surfaces plausible matches, a lightweight text cross-encoder auto-resolves the high-confidence majority, and an agentic multimodal vision-language model settles the ambiguous remainder.
This work introduces a controlled testbed for studying how goal-directed persuaders shift elicited stances in networks of LLM agents grounded in real-world ego-network topologies, and argues for evaluating multi-agent persuasion as a trajectory- and exposure-level process.
A von-Neumann inspired hypothesis of efficient computation as an alternative for neural decoding, a memory-augmented Transformer whose feed-forward block is a low-rank instruction bank: a shared base operator plus a small set of learned low-rank instructions, from which a per-token code synthesizes the weight matrix ac...
SHIFT-LLM, a training-free post-pruning correction framework that inserts a Linear Residual Adapter at each pruning site, consistently recovers accuracy lost to depth pruning across most configurations, achieving gains up to +15.7 points on Llama-3.1-8B-Instruct.
PURPOSE Developmental language disorder (DLD) is linked to long-term academic and social difficulties. Despite these lasting impacts, state-level prevalence estimates are limited. This study estimated prevalence among early-elementary students in West Virginia who may be at risk for DLD and examined variation by grade,...
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A Blog post by Ai2 on Hugging Face
A Blog post by IBM Research on Hugging Face
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