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SenseNova releases SenseNova-Loop-9B-Preview, a looped multimodal model built on a shared looped block and mHC residual stream architecture, targeting long-context and agentic workflows with capabilities spanning motion design, PPT generation, and data analysis.
tinyworldformer runs two tiny neural networks—a looped-transformer world model and an MLP actor—on a Raspberry Pi Pico 2 W to generate and play simple games like Breakout, Pong, and Flappy Bird entirely on-device, with optional on-board RL learning via stream-x.
A community post laying out feature requests for Google's upcoming Gemma 5, including looped transformers for better reasoning, DeepSeek's Engram memory, cheaper KV cache via Compressed Sparse Attention, a potential ~120B MoE variant, drafter improvements, and keeping Gemma well-rounded beyond coding benchmarks.
NVIDIA 发布 Nemotron Labs Dory1.0-4B-BF16，一款 4B 参数的循环式(latent-recurrent)大语言模型，采用 normalized-GPT 架构与滑窗/全注意力混合层，支持弹性推理计算与最后一次循环 KV 缓存，并原生支持 NVFP4 预训练，采用 OpenMDW-1.1 开放许可。
介绍 Looped Diffusion Transformer 论文：通过在每个去噪步骤内重复运行共享的 transformer 块，并结合深度监督和自调制注意力，使 260M 模型以 4.9 倍更少的推理计算超越 6.5 倍大的模型，且循环深度可在采样时调节；作者还用 MIT 开源权重在 M5 Pro 上实测了不同深度的效果。
LoopICL decouples parameter count from depth by using a single weight-tied transformer block with dual cell/row streams and a learned exit gate, matching TabICL v2 on TabArena/TALENT at the same FLOPs while using ~90% fewer parameters.
This paper addresses deployment bugs in the Nanbeige4.2-3B Looped Transformer model on Apple Silicon and introduces a memory-efficient chunked-prefill strategy to enable agentic tasks.
Nanbeige4.2-3B is a compact 3B parameter general agentic model pretrained from scratch with a Looped Transformer, achieving strong agentic and reasoning performance, outperforming larger models on diverse benchmarks. The model and code are open-sourced.
Compares two new AI models for agentic workloads: the compact Nanbeige4.2-3B with a looped transformer architecture and the large Mixture-of-Experts Laguna S2.1, both released on Hugging Face.
Nanbeige4.2 has been released on ModelScope with two models: a 28T-token Looped Transformer base and a 3B SFT+RL agent that reportedly outperforms Qwen3.5-9B and Gemma4-12B on agent benchmarks.
Nanbeige4.2-3B is a new 3B parameter AI model using a looped transformer architecture that outperforms models 4x its size.
Loopie models use a looped transformer architecture to match or exceed Qwen3 Coder 30B performance with only 10% of the pre-training tokens, demonstrating strong reasoning abilities and efficient scaling.
Nanbeige4.2-3B is a compact agentic model using Looped Transformer architecture, demonstrating strong performance on agentic and reasoning benchmarks at the 3B scale, outperforming larger models such as Qwen3.5-9B and Gemma4-12B.
Loopie is a new looped Transformer model that achieves gold-medal performance at the 2025 IMO and IPhO without external tools, using a novel post-training pipeline. It outperforms vanilla Transformers trained with the same compute budget.
Introduces Looped Latent Attention (LLA), a post-training codec that compresses KV cache in looped transformers by exploiting low-rank structure across recurrence steps, achieving significant compression ratios while maintaining performance.
Loopie introduces looped Mixture-of-Experts Transformers that outperform vanilla transformers under the same compute budget, achieving gold-medal performance at the 2025 IMO and IPhO without tools.
This paper identifies gradient oscillation and residual explosion as causes of training instability in Looped Transformers, and proposes Fully Looped Transformer with two parameter-free modifications (Fully Looped Architecture and Attention Injection) to stabilize training up to 12 loop iterations, achieving up to 13.2% improvement in downstream performance.
Proposes Memory-Efficient Looped Transformer (MELT), a novel recurrent LLM architecture that decouples reasoning depth from memory consumption by sharing a single KV cache across loops and using chunk-wise training with interpolated transition and attention-aligned distillation.