This paper presents a multi-stage framework for detecting reclaimed slurs in multilingual social media discourse. It addresses the challenge of identifying reclamatory versus non-reclamatory usage of LGBTQ+-related slurs across English, Spanish, and Italian tweets. The framework handles three intertwined methodological challenges like data scarcity, class imbalance, and cross-linguistic variation
Chain-of-Thought (CoT) reasoning successfully enhances the reasoning capabilities of Large Language Models (LLMs), yet it incurs substantial computational overhead for inference. Existing CoT compression methods often suffer from a critical loss of logical fidelity at high compression ratios, resulting in significant performance degradation. To achieve high-fidelity, fast reasoning, we propose a n
Quantization has become a standard tool for efficient LLM deployment, especially for local inference, where models are now routinely served at 2-3 bits per parameter. The state of the art is currently split into simple scalar quantization techniques, such as GPTQ or AWQ, which are widely deployed but plateau in accuracy at 3-4 bits per parameter (bpp), and "second-generation" vector- or trellis-qu
Modern smart vision sensors need on-device intelligence to process video streams, as cloud computing is often impractical due to bandwidth, latency, and privacy constraints. However, these sensory systems typically rely on ultra-low-power microcontrollers (MCUs) with limited memory and compute, making conventional video object detection methods, which require feature storage or multi-frame bufferi
Agent skills, structured packages of procedural knowledge and executable resources that agents dynamically load at inference time, have become a reliable mechanism for augmenting LLM agents. Yet inference-time skill augmentation is fundamentally limited: retrieval noise introduces irrelevant guidance, injected skill content imposes substantial token overhead, and the model never truly acquires the
Capital signals are distorted by grant-sized entries and nonstandard recipients, so the useful read is concentration rather than startup momentum. The cycle points to large pools of money moving outside the usual venture pattern.
Capital signals are distorted by grant-sized entries and nonstandard recipients, so the useful read is concentration rather than startup momentum. The cycle points to large pools of money moving outside the usual venture pattern.
Capital signals are distorted by grant-sized entries and nonstandard recipients, so the useful read is concentration rather than startup momentum. The cycle points to large pools of money moving outside the usual venture pattern.
Named talent movement is thin, but the roles still matter: infrastructure and research-adjacent hires remain the clearest signal of where teams are reinforcing execution. The desk is more about staffing posture than headline-grabbing departures.
Named talent movement is thin, but the roles still matter: infrastructure and research-adjacent hires remain the clearest signal of where teams are reinforcing execution. The desk is more about staffing posture than headline-grabbing departures.
Named talent movement is thin, but the roles still matter: infrastructure and research-adjacent hires remain the clearest signal of where teams are reinforcing execution. The desk is more about staffing posture than headline-grabbing departures.
A small cluster of benchmark scores lands on the same agentic system, but the cycle does not show a broad evaluation reset. The value here is in tracking whether isolated gains on task suites translate into wider surface area.
A small cluster of benchmark scores lands on the same agentic system, but the cycle does not show a broad evaluation reset. The value here is in tracking whether isolated gains on task suites translate into wider surface area.
A small cluster of benchmark scores lands on the same agentic system, but the cycle does not show a broad evaluation reset. The value here is in tracking whether isolated gains on task suites translate into wider surface area.