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推論系統

Ling-3.0-flash INT4 Hits 38.7 tokens/s in Single-System Testing; Using Mainline vLLM May Silently Produce Incorrect Output

A community deployment recipe running on a single DGX Spark uses CUDA Graph and a one-layer MTP speculative decoder to increase Ling-3.0-flash INT4 generation speed from 20.8 to 38.7 tokens/s. More importantly, it finds that mainline vLLM does not yet support the V3 architecture: forcing the model through an older attention path may not raise an error but can produce plausible-looking yet incorrect content.

代理工具

CalibForge Calibrates 5,431 Terminal Tasks Using Strong and Weak Agents; 35B Model Reaches 47.57% on Terminal-Bench 2.0

Rather than retaining every executable synthetic task, CalibForge repeatedly revises tasks until different solver agents exhibit predefined success and failure patterns. Two models fine-tuned on calibrated trajectories improved across three coding-agent benchmarks, but full training required 64 NVIDIA H20 GPUs, and some results were based on only a single run.

時間序列與檢索增強

TS-RAG Fuses Historical Sequences via Reference Tokens, Reducing Average MSE to 0.310 Across Six Forecasting Datasets

Baidu researchers have adapted RAG from text generation to multivariate time-series forecasting, using a TCN to retrieve similar segments and cross-attention to fuse them. A channel-dependent variant outperformed the listed baselines across six datasets, but the code has not been released, and maintainers have warned that the conventional benchmarks used may no longer be sufficiently discriminative.

最新模型

Vision Models Can Zoom In on Images Without Necessarily Using the Evidence; Qwen3-VL-8B’s Net Gain Is Just 6.9 Percentage Points

A new study uses counterfactual cropping to test six open models, distinguishing between “calling a tool” and “the tool’s returned content actually changing the answer.” Most positive gains are concentrated in a small number of well-calibrated trajectories, suggesting that final accuracy alone may overstate visual tool capabilities.