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DASH Dynamically Allocates Distillation Weights Based on Reasoning Divergence, Raising Qwen3-1.7B’s Math Average by 3.2 Points

Rather than treating teacher–student differences at every token equally, DASH adjusts the scope of supervision based on how divergence changes across an entire reasoning sequence. All three Qwen3 sizes outperform OPSD under the same conditions, but selecting the best checkpoint by average test-benchmark score may overestimate generalization gains.

3D 生成與具身 AI

iARCS Uses LLMs to Generate Reward Programs for 3D Scenes, Reducing the Object Collision Rate from 52.67% to 40.45%

iARCS first corrects collisions and walkability issues in an indoor scene generator, then compiles natural-language requirements into executable reward functions for a second stage of reinforcement learning. In 3D-FRONT experiments, it outperforms MiDiffusion on geometric metrics, but each new requirement requires a separately trained LoRA, and the authors have not yet released an implementation.

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SMRC-SD Verifies Agent State Before Distilling Successful Trajectories, Improving Qwen3-1.7B Task Success Rate by About 12 Percentage Points

Successful demonstrations may not apply to states reached after an agent takes a detour, and unconditionally providing the full trajectory can even reduce the probability of the correct action. SMRC-SD adds a self-distillation signal only when the state is compatible with a demonstration step, outperforming the full-path baseline on both ALFWorld and WebShop.

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ERA’s Reported 11% Edge in Retrospective Epidemic Forecasting Is Reassessed, With Data-Revision Leakage Explaining Nearly All of the Gain

A new analysis finds that Google’s ERA was backtested using season-finalized data, effectively giving it access to revisions that were unavailable to CDC models when their forecasts were made. The two achieved similar Weighted Interval Scores when the data underwent little or no revision, showing that AI forecasting benchmarks must preserve the version of the data available at each point in time.

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Cloudflare Launches Kitesurf: Lightweight Web Engine Replaces Chromium, Cutting Resource Usage for Agentic Browsing to About One-Third or Less

Kitesurf brings Rust, Wasm, and modular Web components to Cloudflare Workers, reducing browser overhead for agent workloads such as content extraction, form interaction, and screenshots. Cloudflare claims that some tasks use 3 to 7 times less CPU and memory in its tests, though website compatibility, anti-bot verification, and source-code availability remain major limitations.