AI·llama.cpp build b9966 fixes regex recompilations for -sm tensor mode, caching patterns per tensor to reduce CPU overhead on decode threads.
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AI·User with RTX 4090, 3090Ti, and 128GB RAM struggles to run larger models like 122B due to VRAM limits while Qwen3.6-27B runs efficiently without using system RAM.
AI·Shares tool for tweaking models' J-Space using Anthropic Jacobian-Lens to create super harmful behavior.
AI·The paper identifies a failure mode in critic-free RL methods for LLMs where implausible tokens receive uniform credit, and proposes tail-aware credit calibration to improve reinforcement learning.
AI·The paper proposes an agentic tool-making pipeline that compiles repeated SOP steps into validated versioned tools to reduce latency and improve reliability in production LLM agents.
AI·A researcher has pre-trained a 500M parameter LLM on 160GB of 1800-1875 English texts and plans to train a 2B model, with the evaluation version demonstrating promising historical knowledge recall.
AI·UniClawBench is the first capability-driven benchmark for proactive agents, using live Docker containers and closed-loop multi-agent evaluation to assess five foundational skills across 400 real-world tasks.
AI·Canvas360 is a two-stage in-context panoramic generation framework with geometry-aware pretraining and a 1M-sample dataset, supporting style transfer, inpainting, outpainting, and editing tasks.
AI·SAM-MT extends Segment Anything 2 for real-time interactive multi-target video segmentation, improving FPS by jointly processing multiple targets instead of replicating single-target pipelines.
AI·Single-Rollout Asynchronous Optimization is an agentic RL method that replaces group-wise sampling with single-rollout updates and adds token-level clipping to improve stability and performance on coding and reasoning benchmarks.
AI·Talos-XII is a Rust-based CLI simulator for Arknights: Endfield gacha probabilities that trains small neural nets for uncertainty modeling and decision policies without using PyTorch or tch-rs.
AI·UP is a universal RL objective that breaks the exploration-stability dilemma by allowing unclipped positive gradients while clipping negative ones, enhancing exploration without sacrificing training stability across various RL frameworks.
Samsung Electronics deploys ChatGPT Enterprise and Codex to employees worldwide, marking one of OpenAI’s largest enterprise AI rollouts.
Doing a bachelor thesis on fine-grained car classification (telling apart VW Golf generations from listing photos). Simple setup: frozen encoder → embeddings → weighted k-NN. On my small dataset (175 train / 132 test): I thought maybe it was a cosine vs euclidean thing, but my embeddings are L2-normalized so both give the same ranking. Tried both, DINOv2 stays at 41%. I get that SigLIP was traine…
Inference-time scaling for text-to-image generation has progressed from simple Best-of-N (BoN) sampling to guided search methods that verify and steer candidate trajectories at intermediate denoising steps. These approaches focus on when and how often to verify during denoising but largely treat the cost of generation itself as fixed. Moreover, the standard practice of comparing methods by number of function evaluations (NFEs) counts only denoising forward passes and ignores verifier overhead, …
Modern one-step diffusion models achieve impressive quality through distribution-based timestep distillation. Yet, they rely on a critical assumption: Teacher and Student must inhabit the same latent space. This Shared-Space constraint prevents knowledge transfer from modern high-capacity Teachers (e.g., SD 3.5 and Flux) into compact, deployment-friendly Students such as SD 1.5, whose latent resolution and VAE parameterization differ from the Teacher. We formalize this overlooked regime as Cros…