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1542 technical news articles

代理工具

OSReward Finds That Computer-Agent Judges Commonly Let Failed Trajectories Pass, While Visual Evidence Has Surprisingly Limited Impact on Verdicts

Using 1,019 human-reviewed cross-platform trajectories, OSReward tested 27 vision-language judges and found that their main error was classifying incomplete tasks as successful. Removing step-by-step text reduced accuracy by an average of 7.2 percentage points, while changing the visual inputs had a smaller effect, exposing current “visual judges’” reliance on agents’ self-reported narratives.

最新模型

PerceptionBench Breaks Visual Reasoning Back Down into Ten Basic Perceptual Skills; None of 16 Multimodal Models Scores 60%

Moonshot AI built a taxonomy of perception failures from the earliest points of failure across 42 existing benchmarks, then used 3,000 short-answer questions to isolate ten basic visual capabilities. The results show that models with similar overall scores can have entirely different perceptual gaps, but because the test set was drawn from a larger internal question pool, contamination and evaluator bias remain concerns.

最新模型

Mage-VL Selects Visual Tokens Directly from Video Encoding Data, Accelerating Streaming Multimodal Inference by Up to 3.5×

Microsoft’s Mage-VL replaces uniform video frame sampling with I/P frames, motion vectors, and residual energy, encoding only regions with significant changes. Its 4B model reportedly reduces visual tokens by more than 75% while preserving performance on static tasks, although speed and quality comparisons still come primarily from official tests.

機器人與具身 AI

HiFi-UMI Trains Robots Directly on Millimeter-Accurate Wearable Data, Eliminating the Need for Real-Robot Demonstrations in Post-Training

HiFi-UMI combines offline stereo-inertial SLAM, microsecond-level synchronization, and six-view bimanual capture in a portable data system, enabling human-only manipulation data to be used directly for robot post-training. Real-world success rates across three VLA/world-action models approached an in-situ teleoperation baseline, though the results remain limited to controlled tasks evaluated by a single team.

實體 AI/科學自動化

PUDA Connects Laboratory Agents Through a Constrained CLI and Event Logs, Isolating Generative Planning from the Hardware Driver Layer

PUDA exposes automated instruments as discoverable command-line tools and uses JSON, NATS/JetStream, and stable identifiers to preserve commands, measurements, and sample provenance. Agents can choose the next experiment, but actual hardware operations can occur only through engineer-authored driver methods with validated parameters.

代理工具

CAPA Tests Cross-Session Memory in Coding Assistants: Same-User History Raises First-Try Success by 15.6 Points on Average

CAPA embeds implementation preferences that users repeatedly omit into 600 executable coding tasks, testing whether assistants can infer new requirements from past conversations. Across 12 models, adding same-user history increased final success rates by only 6.8 points on average, but raised first-try success by 15.6 points—suggesting that memory mainly reduces clarification rounds rather than eliminating failures.