Knowledge catalogue
arXiv:2507.07920v2 Announce Type: replace-cross Abstract: Cerebrovascular research heavily relies on quantitative analysis of intracranial arteries from time-of-flight magnetic resonance angiography,
arXiv:2606.25207v1 Announce Type: cross Abstract: Hyperparameter Optimization (HPO) is essential for maximizing machine learning model performance, and its core challenge is sample efficiency: finding
arXiv:2606.25128v1 Announce Type: cross Abstract: Volume and quality of datasets are crucial for deep learning model training, yet they are often constrained by availability and data acquisition costs
arXiv:2606.25421v1 Announce Type: new Abstract: Recent studies on world modeling for Large Language Model (LLM) agents typically formulate the learning objective as next-observation prediction. Howeve
arXiv:2512.00727v2 Announce Type: replace Abstract: Reinforcement learning has enabled impressive locomotion skills on articulated robots, but common policy representations remain only weakly aligned
arXiv:2606.25056v1 Announce Type: new Abstract: Behavioral Foundation Models (BFMs) offer a promising path toward universal physics-based character control by organizing a rich repertoire of physicall
arXiv:2505.12843v2 Announce Type: replace Abstract: Reinforcement Learning from Human Feedback (RLHF) relies on reward models to align large language models with human preferences. However, RLHF often
arXiv:2606.25473v1 Announce Type: new Abstract: Autoregressive video diffusion with causal diffusion transformers has emerged as a major paradigm for real-time streaming video generation and action-co
Chad Jones, economist who'll be joining Anthropic: 'In other words, with log utility it is optimal to take a 1 in 3 chance of ending human existence in exchange for a 2/3 chance of dramatically raisin
Chart of increasing revenue, pre the decline of token-maxxing, not looking at the immense costs/lack of profitability, not considering threats from open-source models, price-war dynamics etc. @noahopi
arXiv:2606.25386v1 Announce Type: new Abstract: By maintaining global consistency across robot teams, multi-robot LiDAR map merging enables faster exploration and efficient area coverage. However, map
arXiv:2606.25293v1 Announce Type: new Abstract: Positional encodings (PEs) are essential for Transformers. Yet designing effective PEs for non-Euclidean graphs remains challenging. Such encodings shou
arXiv:2510.17059v2 Announce Type: replace Abstract: Zero-shot imitation learning requires an agent to reproduce expert behavior from a single demonstration without additional environment interaction o
arXiv:2512.22487v2 Announce Type: replace Abstract: The design of Korean constituency treebanks raises a central representational question concerning the choice of terminal units. Although Korean word
arXiv:2507.09052v3 Announce Type: replace Abstract: Training data for class-conditional image synthesis often exhibit a long-tailed distribution with limited amount of images for tail classes. Such an
Crazy how many times people have told me over the last five years that a solution to hallucinations was right around the corner — and yet here we still are. This study tests how often LLMs invent answ
arXiv:2606.25483v1 Announce Type: new Abstract: Path-traced synthetic stereo data underlie a large fraction of modern disparity-estimation training pipelines. We report a previously unrecognised prope
arXiv:2606.16497v2 Announce Type: replace-cross Abstract: GPU kernel optimization represents a paradigm where functional correctness is assumed and execution efficiency is the objective. We present da
arXiv:2606.25360v1 Announce Type: new Abstract: While end-to-end Vision-Language-Action (VLA) models show promise in robotic manipulation, their monolithic paradigm inherently couples semantic reasoni
arXiv:2606.26048v1 Announce Type: new Abstract: Soft robots are challenging to control due to their nonlinear and time-varying dynamics. Data-enabled predictive control (DeePC) offers a model-free alt
arXiv:2606.25939v1 Announce Type: new Abstract: Demonstration augmentation is proposed for cost-efficient data acquisition, but existing methods are fundamentally limited in deformable manipulation du
arXiv:2606.24954v1 Announce Type: cross Abstract: Vibration-based health monitoring of rotating machinery requires reliable fault diagnosis under operational data constraints, yet condition assessment
arXiv:2605.25661v2 Announce Type: replace Abstract: Current mainstream methods of aligning diffusion models with human preferences typically employ VLM-based reward models. However, these reward model
arXiv:2606.25254v1 Announce Type: cross Abstract: Maternal-fetal US is the primary imaging modality for monitoring fetal development, yet accurate automated segmentation remains challenging due to the
arXiv:2606.25295v1 Announce Type: new Abstract: Mobile manipulation is a fundamental robotics task and has advanced rapidly in recent years, enabling robots to navigate, reach, and interact with objec
arXiv:2606.25197v1 Announce Type: new Abstract: Learning effective policies for adaptive data acquisition remains challenging: posterior-based methods rely on surrogate models and posterior approximat
arXiv:2606.25284v1 Announce Type: new Abstract: Camera-based monitoring systems are increasingly adopted in healthcare settings for the continuous assessment of patient movement and activities. Howeve
Secure software supply chain solution provider Chainguard Inc. today expanded its Chainguard Repository product with malware scanning, policy enforcement and visibility features that now cover Java pa
arXiv:2606.25923v1 Announce Type: new Abstract: A digital twin (DT) is a virtual model of a real-world system that can assist decision-making by simulating scenarios induced by different policies. How
arXiv:2606.19190v2 Announce Type: replace Abstract: Robust state estimation and mapping in long-term, large-scale, and highly dynamic environments remains a key challenge in robotics. Existing LiDAR-I
arXiv:2606.25344v1 Announce Type: new Abstract: 4D generation aims to animate 3D objects with realistic motion, holding great promise for applications. Existing methods typically decouple 3D asset gen
arXiv:2606.26006v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are often constrained by the imitation ceiling imposed by sub-optimal data. While Reinforcement Learning (RL) fine-t
arXiv:2606.26093v1 Announce Type: new Abstract: Human demonstrations are a scalable data source for learning robot manipulation policies. However, common sources of human demonstration data, such as m
arXiv:2502.18959v4 Announce Type: replace Abstract: The architecture of a neural network and the choice of its activation function are both fundamental to its performance. Equally important is ensurin
arXiv:2505.19532v2 Announce Type: replace Abstract: The current state-of-the-art backdoor attacks against Reinforcement Learning (RL) rely upon unrealistically permissive access models, that assume th
arXiv:2606.24996v1 Announce Type: new Abstract: Forecasting leaderboards rank models by predictive quality, but their winners are often read as deployment-ready top-1 advice. That reading can fail whe
arXiv:2606.25460v1 Announce Type: cross Abstract: Recent advances in sequence modeling have significantly improved ASR systems, bringing them close to human-level recognition accuracy and enhancing ro
arXiv:2606.25073v1 Announce Type: new Abstract: In cooperative multi-agent reinforcement learning (MARL), from a deployment perspective, it is challenging and expensive to train agents from scratch fo
arXiv:2512.01085v3 Announce Type: replace-cross Abstract: Medical phrase grounding (MPG) maps textual descriptions of radiological findings to corresponding image regions. These grounded reports are e
arXiv:2606.25347v1 Announce Type: cross Abstract: Exemplar-free class-incremental learning (EFCIL) requires stable decision boundaries within a shifting feature space. While maintaining class-conditio
Grifters and many other salesman are like LLMs. They say things that aren’t always true with absolutely certainty. Bitcoin has won. Global consensus is that $BTC is digital capital. The four-year cycl
Grok may not be the AGI that Elon promised, but it appears that the man has found his use case. xAI is betting big on AI video and image generation — but the biggest driver of Grok Imagine may not be
arXiv:2606.25198v1 Announce Type: new Abstract: Autonomous AI Research promises to accelerate the scientific progress of machine learning. To realise this goal, current Large Language Model (LLM)-base
arXiv:2501.02211v2 Announce Type: replace-cross Abstract: Large language models (LLMs) reproduce homogeneity bias -- the tendency to portray marginalized groups as more internally similar than dominan
Imagine if i had a business that gave you 20 bills for 10 bills. As word spread, my customer base would grow. My revenue (how many $10 bills I collected) would grow. And I would continue to lose money
In the end, will Elon be best known for his efforts to mainstream electric cars, for his rockets, …. or for his efforts to mainstream AI-generated porn? xAI is betting big on AI video and image genera
It is amazing to me how little the X-verse cares about the rise of authoritarianism in the United States. Is that because most of the “people” here are actually Russian bots? 🤔 More Soviet-style decep
arXiv:2606.26095v1 Announce Type: cross Abstract: Most Vision-Language-Action (VLA) models build on a Vision-Language Model (VLM) backbone by attaching an action module and optimizing the full policy
arXiv:2606.25706v1 Announce Type: new Abstract: High-level humanoid planners often output sparse task-space, low-rate trajectories, whereas whole-body controllers run at high frequency. This creates t
arXiv:2606.25362v1 Announce Type: cross Abstract: Sequential contextual stochastic programs model real-time decision systems in which each time epoch commits to an action under uncertainty whose conse
arXiv:2606.26047v1 Announce Type: new Abstract: Robot crowd navigation requires the ability to infer human intentions while accounting for the structural constraints of the environment. Currently, dee
arXiv:2606.25665v1 Announce Type: new Abstract: Domain generalization (DG) aims to learn a model from one or more source domains that generalizes to an unseen target domain without accessing target da
arXiv:2606.25451v1 Announce Type: new Abstract: Estimating token-level advantages in reinforcement learning (RL) for language models remains challenging because scaling up episodic experience collecti
arXiv:2606.25401v1 Announce Type: cross Abstract: Accurate channel state information (CSI) prediction is essential for proactive beamforming and resource management in 5G massive MIMO systems, yet the
arXiv:2606.25057v1 Announce Type: new Abstract: The rapid growth of scientific submissions has pushed traditional peer review toward its scalability limits, motivating the exploration of large languag
Looks like OpenAI’s IPO will be delayed until 2027. • might be a sign that their finances don’t look compelling yet. • gives Anthropic time to go first If they can bump up the valuation by $999.3 bill
love that one of my readers made her own, explicit set of public predictions. 🙏 I want to post my predictions for 2ish years horizon. AI stock bubble collapses due to fundamentals not working out with
arXiv:2606.25593v1 Announce Type: new Abstract: We study optimal-policy geometry in structured Markov decision processes. While approximate dynamic programming and reinforcement learning typically app
arXiv:2606.25526v1 Announce Type: new Abstract: Cooperative multi-agent reinforcement learning assumes each agent shares the same reward function and can be trained effectively using the Trust Region
arXiv:2606.25398v1 Announce Type: new Abstract: Reward design remains a major bottleneck in reinforcement learning for robot locomotion, where successful policies often depend on carefully tuned, task