AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：How text diffusion models rethink language generation—and the tradeoffs that will determine their future.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Former deputy PM now involved in tech industry says many within the sector are ‘winding themselves up into a lather’ UK politics live – latest updates Nick Clegg has dismissed fears over AI’s “godlike power to exterminate humanity”, calling it a sign that tech bosses are “breathing their own fumes”. The former UK deputy prime minister said that tech bosses should focus on addressing known “specific threats” such as cybersecurity, bio-weapons and emotional dependence rather than the “slightly hand-wavy view that this technology is unavoidably going to develop some godlike power which is going to turn on us and exterminate humanity”. Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：A belated discussion of Astra’s release, a bunch of AI incidents, and the broader situation we are in with regards to AI safety.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Google is reportedly nearing the launch of its long awaited Gemini 4 model, after dawdling behind rival developers on flagship AI releases. Speaking with The Information during his first media appearance as the leader of Google's DeepMind division, Koray Kavukcuoglu said that Gemini 4 is currently in its refinement stage, and that the company is aiming to launch the model "much earlier" than the end of the year. "Our intention is to, like - as soon as possible - to release an early post-training output because we see the results and we are excited," Kavukcuoglu told the publication, adding that Google would "continue the fast-paced iteratio … Read the full story at The Verge.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：In the choreographers’ new work, virtuosic movement and some green-screen magic unfurl the theatricality of high-stakes television interviews It appears the interviewer has got him on the ropes. “For the record, I did not take part in a pagan ceremony with minor members of the royal family in which we daubed ourselves in paint,” states the beleaguered politician, caught outside Buckingham Palace with his flies undone and forced to defend himself. This is a fabrication, of course – I’m watching the scene play out in an east London dance studio – but it doesn’t feel miles away from something that could be true. And how do we know what’s the truth anyway? That’s the question in Deepfake, the latest piece from award-winning dance duo Jessica Wright and Morgann Runa…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Team Zuck is absolutely on fire.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：All Australians should demand independent means to protect ourselves from Dr Sam Altman Frankenstein and Daddy America Whoopsie! Dr Sam Altman Frankenstein regrets to inform you he’s lost control of his OpenAI monster. It’s roving around doing things that provoke international legal investigation, and Australia has found out in the worst possible way. Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Contrastive-LM has released CLM-8B, an open System One model that scores candidate actions against a state instead of generating text. It adds 2 small projection heads to a frozen Qwen3-8B encoder and trains them with a contrastive InfoNCE objective. In zero-shot tests it runs up to 9× faster than TypeSafe's Jev. With fine-tuned heads as a verifier, it reaches 81.6% on held-out DeepSWE tasks and 87.6% on held-out Terminal-Bench 2.1 tasks. The post Contrastive-LM Releases CLM-8B: An Open System One Model That Scores Agent Actions Up to 9× Faster Than Jev appeared first on MarkTechPost.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Experts say ‘fairly minor’ breach is a portent of things to come and proprietary closed systems like OpenAI are ‘the least of the worries’ Follow our Australia news live blog for latest updates Get our breaking news email, free app or daily news podcast Anthony Albanese says an artificial intelligence agent developed by OpenAI hacked Medicare and three other systems in June – and the company only notified Australia earlier this month. The prime minister has expressed his “extreme concern” over the incident, although he noted no personal information is believed to have been accessed in the breach. Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：The year’s most popular slang reveals what young people think about artificial intelligence – and it’s not positive Name: “That’s AI!” Age: Brand new. Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.27068v1 Announce Type: new Abstract: Pre-trained robot policies always require finetuning to adapt to specific environments. Reinforcement Learning (RL) offers high performance potential because it improves action optimality rather than simply mimicking data. However, such potential depends heavily on reward quality. Sparse rewards lack process feedback, human-designed rewards are costly and biased, and semantic rewards from foundation representations are often not control-centric. We propose Hindsight Reward Editing (HiRE), a training-free framework to break this reward bottleneck. HiRE bridges the broad knowledge of foundation representation models with physical control awareness, by contrasting successful and failed trajectories in hindsight. It c…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.27006v1 Announce Type: new Abstract: We present a laser-tracker-assisted hand-eye calibration method for camera-equipped mobile robots. The method combines laser-tracker-based 3D metrology with camera-based 2D observations. Building on our previous laser-tracker-assisted camera-to-robot calibration method for ground-observing mobile robots, we present a generalized formulation for calibrating the camera pose in the coordinate system of tracker-localized mobile robots. The new approach relaxes assumptions of our previous method on robot and camera configuration by chaining multiple calibration targets resulting in a more general approach supporting various camera-equipped mobile robot systems.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.27005v1 Announce Type: new Abstract: We focus on the problem of rearranging multiple objects within a constrained workspace via pushing using a team of car-like robots. While the use of multiple robots offers the potential for more efficient execution, the need for conflict resolution and the kinematic constraints arising from physics, robot design, and the workspace boundary make this problem especially challenging. Our key insight is that by exploiting the structure introduced by the car-like kinematics of the domain, we could relax the problem into an ordered assignment of Dubins curves to robots. To this end, we introduce MultiPush, a reinforcement-learning based framework that jointly determines an efficient schedule of pushing tasks and their a…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.27003v1 Announce Type: new Abstract: Runway walking requires coordinated control of posture, stride, foot placement, and whole-body motion to effectively present clothing and convey a distinctive style. However, humanoid robots used in fashion shows typically rely on locomotion policies optimized primarily for stability and walking speed, limiting their ability to reproduce expressive, human-like runway motions. In this work, we present an end-to-end framework that transforms monocular runway videos into deployable humanoid locomotion policies through motion recovery, robot retargeting, motion correction, policy training, simulation-based evaluation, and physical deployment. We evaluate the proposed framework on the Booster K1 humanoid robot using ru…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.27001v1 Announce Type: new Abstract: We investigate humanoid locomotion with a fly-inspired recurrent controller and identify the pathways supporting its deployed behavior. The controller couples 3,609 continuous neural states to a simulated Unitree G1 through body-observation projections, a motor-neuron-labelled readout, and joint servos. We formulate this neural-body feedback system and evaluate a fixed checkpoint across seven terrain instances, three speeds, and three initial yaw offsets. It completes 61/63 conditions under a survival-and-forward-progress criterion; a privileged reference completes 62/63. At nominal yaw, resetting the recurrent motor state before every policy call changes success from 19/21 to 0/21. Conversely, depth and upstream-…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.26989v1 Announce Type: new Abstract: Hexapod robots can achieve static stability with fewer actuated joints than bipeds or quadrupeds, yet many platforms still use 3-DOF legs, increasing weight and continuous torque requirement with limited gain in locomotion capability on flat, inclined and moderately rough terrains. We release Spiderbot, an open-source hexapod that uses a 4-bar linkage with a passive spring to mechanically support body weight, with a 2-DOF per-leg design that substantially reduces energy consumption. This mechanism substantially offloads gravitational torque during standing stance consuming only 1.5W (reduction of over 90\% over the unsprung version and up to 96\% over other similar hexapods). The passive spring compensation extend…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.26919v1 Announce Type: new Abstract: Event cameras promise low-latency perception for high-speed robotic systems, where even short delays can render detections stale by the time they inform downstream robotic decisions. Yet modern event detectors still require tens of milliseconds of computation before their predictions become available. Conventional evaluation ignores this delay by comparing predictions with annotations at the observation timestamp, even though the scene may have changed by the time those predictions are produced. We study this observation-availability mismatch in event-based multi-object detection and show that state-of-the-art event detectors degrade substantially when evaluated at prediction availability rather than observation t…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.26872v1 Announce Type: new Abstract: Musculoskeletal (MSK) humanoids provide a physiologically grounded embodiment for studying full-body motor control, but their high-dimensional muscle actuation, delayed activation dynamics, and redundant muscle--tendon structures make learning substantially harder than torque-driven humanoid control. Existing MSK benchmarks remain fragmented across gait, prosthetics, dexterous hands, or challenge-specific tracks, leaving full-body muscle-actuated control insufficiently evaluated under standardized tasks, methods, and metrics. We introduce MSK-Bench, a benchmark of 22 full-body motor-control tasks organized into three progressively challenging categories: postural stabilization, common locomotor behaviors, and cont…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.26868v1 Announce Type: new Abstract: Learning-based models (e.g., visuomotor and Vision-Language-Action (VLA)) are increasingly explored for industrial robotic manipulation, where model predictions are directly translated into physical actions. This tight coupling between model behavior and physical execution makes hidden security vulnerabilities particularly consequential. While backdoor attacks have been widely studied in conventional AI models, their effects on deployed learning-based robotic arm manipulation systems remain less understood: a backdoored robot can behave normally during benign operation while inducing attacker-specified behaviors only when specific triggers are present, posing potentially serious risks in physical environments. In…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.26857v1 Announce Type: new Abstract: Navigation in off-road conditions is challenging due to the lack of structure. There is no fixed vocabulary for what is traversable. The traversability depends on both the environment and the embodiment's dynamics. Neither of these two variables can be hand-labeled at scale. Thus, traversability has to be learned by the embodiment's own experience. Modern platforms tend to use multiple sensors to estimate traversability and navigate: RGBD cameras, lidar, radar, IMU, with computationally intensive platforms to run inference on neural networks. Against this trend, we propose FLINT, a lightweight traversability estimator: a 21.6M-parameter backbone, 38\times smaller than a comparable foundation-model backbone, that s…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.27110v1 Announce Type: new Abstract: Vision-language models (VLMs) are deployed as zero-shot judges of image aesthetics, and panels of several models are recommended, on thin evidence, as the way to make such judges reliable. On two human-rated datasets, EVA and PARA, we find that a panel of holistic judges never significantly beats its best member, whether the verdicts are averaged or fused by a learned combiner. What a panel is worth depends on what it is fed. We therefore have each model score each image on the five dimensions of a frozen, human-written rubric and fuse those scores, alongside each model's verdict, across model families with an out-of-fold combiner. The dimension scores measure what their labels claim: with the overall human score…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.27076v1 Announce Type: new Abstract: Open-vocabulary visual grounding enables robots to localise task-relevant entities from natural-language queries without dependence on predefined perceptual taxonomies. However, existing benchmarks largely rely on short category labels and web-scraped imagery, leaving it unclear whether open-vocabulary models can robustly ground diverse queries and visual conditions under real deployments. We introduce \textbf{Pro-Bench}, a prompt-conditioned benchmark for open-vocabulary visual grounding in heterogeneous, real-world environments. Pro-Bench includes $13k+$ RGB frames from independent robotic domains (subterranean, industrial, indoor, outdoor, urban), with $74.5k$ manual instance annotations and $515$ target querie…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.27022v1 Announce Type: new Abstract: In this paper, we investigate the impact of adversarial attacks on identity encoders within a realistic de-identification framework. Our experiments show that the transferability of attacks transfers from an external surrogate model to the system model (e.g., CosFace to ArcFace) allows the adversary to cause identity information to leak in a sufficiently sensitive face recognition system. We present experimental evidence and propose strategies to mitigate this vulnerability. Specifically, we show how fine-tuning on adversarial examples helps to mitigate this effect for distortion-based attacks (i.e., snow, fog, etc.), while a simple low-pass filter can attenuate the effect of adversarial noise without affecting th…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2609.27015v1 Announce Type: new Abstract: We developed an anatomy-aware deep learning framework to synthesize post-contrast breast MRI from pre-contrast images, emphasizing tumor and background parenchymal enhancement (BPE) regions. This retrospective study included 649 patients with 6,251 paired pre-contrast and post-contrast images. The framework integrates breast mask consistency, lesion-region supervision, and BPE-region supervision into an image-to-image translation model. Evaluation included quantitative image quality metrics, a reader study with two breast radiologists, and downstream Ki-67 classification. The proposed method outperformed Pix2Pix, Pix2PixHD, diffusion-based synthesis, and mask-supervised baselines in whole-image and regional evalua…