AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,468 papers
A novel and scalable framework that rewrites a coding agent's context as the repository changes rather than as the context grows, and can achieve a higher resolve rate in all experiments spanned by six coding agents and three edit-heavy benchmarks with little computational overhead.
This work introduces Structured Matrix Attention via a family of causal masks with structured long-range routing whose row supports have VC-dimension, which makes VC-dimension an explicit knob governing access-pattern complexity, prefill cost, and decoding memory.
This work proposes a large-scale multimodal large language model-based supervision generation framework that improves supervision diversity, fidelity, and semantic coverage, and introduces a granularity-aware text representation with separate CLS tokens for summary and detailed views.
Backdoor as Probe is proposed, a test-time adversarial defense for CLIP that improves average robust accuracy from 1.0\% to 52.3\% while retaining clean accuracy, achieving performance comparable to state-of-the-art methods with up to a \(5.7\times\) inference speedup.
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A novel end-to-end framework integrating a self-attention mechanism to address limitations in effectively detecting small animals in low-contrast trap images and small animals while also demonstrating zero-shot detection capability leveraging the MLLM.
InvPT applies semantic-preserving transformations to the corpus and combines masked language modeling with multi-positive supervised contrastive learning that treats all augmentations of the same source function as positives, mixing self-contrast pairs with invariant-contrast pairs for positives of varying difficulty.
This work introduces Path2Spec, a divide-and-conquer framework that leverages LLMs to extract all execution paths from an input program, generates path-specific specifications for each, and merges them into a comprehensive overall specification.
Test-Time Training (TTT) adapts models to incoming test samples (e.g. out-of-distribution, (OOD)) when conventional fine-tuning is infeasible. Existing TTT methods for Vision-Language Models (VLMs) create supervision from several augmented views, each requiring forward (and often backward) passes through the entire VLM...
Reasoning vision-language models (VLMs) process images and videos as long sequences of visual tokens, making inference expensive. Training-free token pruning reduces this cost, but aggressive compression can sharply degrade performance, often attributed to irreversible loss of task-relevant visual information. We show...
Neural audio codecs (NACs) are widely used in speech generation and audio-language modeling, yet how they encode speaker-trait information remains poorly understood. Prior work applied sparse autoencoders (SAEs) to investigate accent information in NACs through task-level analysis. Here, we extend this analysis to the...
An e-commerce–based sales information system that helps improve the efficiency of transaction management, enhances the quality of customer service, and simplifies the process of ordering and making online payments is designed and developed.
The shock of a collision gets smaller the longer the distance over which one stops. That is why cars are built to crumple on purpose. Varying the stopping distance and the shape of the force, how much the peak acceleration and HIC15, a criterion used for head injury, fall is counted. No new theorem or law is claimed. S...
A Blog post by IBM Granite on Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Gemini 4 Carbon is our strongest model with state-of-the-art cybersecurity and long horizon capabilities.
A Blog post by Liquid AI on Hugging Face
Genie 4: our new world model unlocking unprecedented realism in real-time simulation.
Generative AI
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