Knowledge catalogue
arXiv:2606.23694v1 Announce Type: new Abstract: Graph-based text classification models typically rely on local neighborhood aggregation and overlook global community structure, despite semantic docume
More than 4.7 million people in the US have lost their Supplemental Nutrition Assistance Program benefits, also known as food stamps, since Trump’s signature tax and spending law took effect last July
arXiv:2606.24366v1 Announce Type: new Abstract: We present MorfFlex, a morphological dictionary architecture suitable for languages with extensive regularity in both inflection and derivation. As the
arXiv:2606.24214v1 Announce Type: new Abstract: Accurate pulmonary vessel segmentation remains challenging due to the sparse, tortuous, and multi-scale nature of vascular structures, where small branc
arXiv:2606.24263v1 Announce Type: new Abstract: Microwave satellite imagery plays a crucial role in monitoring tropical cyclone precipitation and intensity worldwide, but suffers from long revisit tim
arXiv:2606.24567v1 Announce Type: new Abstract: Sparse-view computed tomography (SVCT) reduces radiation exposure and acquisition time, but the limited number of projection views makes the reconstruct
arXiv:2504.17070v3 Announce Type: replace-cross Abstract: Robots need task planning methods to achieve goals that require more than one action. Recently, large pretrained models have demonstrated impr
arXiv:2606.24087v1 Announce Type: new Abstract: Reconstructing continuous speech from scalp electroencephalography (EEG) remains fundamentally challenging. EEG provides a weak, spatially diffuse, and
arXiv:2606.24879v1 Announce Type: cross Abstract: We study the last iterate of the stochastic subgradient method for one-dimensional convex Lipschitz objectives. For a fixed horizon n, we consider the
arXiv:2606.24799v1 Announce Type: cross Abstract: Generic text-to-video models can be used as rich open-world scene priors. Despite the high quality of today's generated videos, they do not directly y
arXiv:2606.24447v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have revolutionized document parsing by enabling end-to-end mapping from images to structured text, imposing a significant
arXiv:2606.24396v1 Announce Type: new Abstract: Large Transformer models function as Dense Associative Memories (DAMs), retrieving knowledge via high-dimensional attractor dynamics driven by the self-
arXiv:2606.24267v1 Announce Type: cross Abstract: While in-context learning is generally shown to be effective in Large Language Models (LLMs), bad contexts can cause performance degradation and mode
arXiv:2606.24102v1 Announce Type: new Abstract: Most electronic health record (EHR) foundation models encode clinical events as discrete event tokens from a fixed vocabulary and therefore cannot direc
arXiv:2606.24773v1 Announce Type: new Abstract: Non-autoregressive generation offers a powerful paradigm for iterative refinement, allowing models to recursively critique, erase and regenerate arbitra
arXiv:2603.08287v2 Announce Type: replace-cross Abstract: We analyze the Bayesian regret of the Gaussian process posterior sampling reinforcement learning (GP-PSRL) algorithm. Posterior sampling is a
arXiv:2508.16650v3 Announce Type: replace-cross Abstract: Brain tumour MRI typically requires both pre- and post-contrast imaging, but gadolinium is not always desirable (frequent follow-up, renal imp
arXiv:2606.24093v1 Announce Type: cross Abstract: We ask whether the geographic origin of Tang-dynasty poets leaves a detectable linguistic trace in their work. Aggregating every poem attributed to ea
arXiv:2606.23940v1 Announce Type: cross Abstract: Droplet impact on solid surfaces is a complex fluid dynamics problem with applications in spray cooling, inkjet printing, and pharmaceutical processin
arXiv:2606.24313v1 Announce Type: new Abstract: AI-driven image-to-image synthesis is rapidly advancing, with growing applications in medical imaging. Multi-modal image analysis plays a crucial role i
arXiv:2606.24251v1 Announce Type: new Abstract: Large language models exhibit a growing range of misaligned behaviors such as strategic deception, sandbagging, and self-preservation. As they are incre
arXiv:2606.23879v1 Announce Type: cross Abstract: Purpose: To evaluate the feasibility and challenges of heart chamber segmentation from non-contrast CT scans using contrastive unpaired image translat
arXiv:2606.24625v1 Announce Type: new Abstract: Class imbalance poses a significant challenge in classification, where existing methods such as SMOTE often generate low-quality synthetic samples in re
arXiv:2606.23695v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds Large Language Models in external knowledge, yet current evaluations rely on discrete heuristics that suf
arXiv:2606.23715v1 Announce Type: cross Abstract: A Markov Logic Network (MLN) is a probabilistic relational model used in Statistical Relational Artificial Intelligence for defining a probability dis
arXiv:2605.03940v4 Announce Type: cross Abstract: We describe a dynamical system in which a symbolic field is coupled to a geometric field via a bipartite Hilbert-Schmidt kernel. The system is fully d
arXiv:2603.01346v2 Announce Type: replace Abstract: We revisit the framework of Smart PAC learning, which seeks supervised learners which compete with semi-supervised learners that are provided full k
arXiv:2510.00866v3 Announce Type: replace-cross Abstract: Large-scale models are pretrained on massive web-crawled datasets containing documents of mixed quality, making data filtering essential. A po
arXiv:2606.16845v2 Announce Type: replace-cross Abstract: Small-scale Large Language Models (LLMs) natively default to literal semantic interpretations, making few-shot irony detection a persistent ch
arXiv:2606.24441v1 Announce Type: new Abstract: We present S1-Omni-Image, an open-weight unified multimodal model for scientific image understanding, generation, and editing. Unlike general-purpose im
arXiv:2606.24610v1 Announce Type: new Abstract: The evaluation of cultural grounding context becomes complex when multiple cultures convey the same moral lesson. This challenge is particularly relevan
arXiv:2508.17728v2 Announce Type: replace Abstract: Cervical cancer remains a significant global health concern and a leading cause of cancer-related deaths among women. Early detection through Pap sm
arXiv:2606.24077v1 Announce Type: new Abstract: Contextual entrainment, which is a newly discovered phenomenon in large language models (LLMs), refers to the tendency of a model to assign higher proba
arXiv:2602.16568v2 Announce Type: replace-cross Abstract: Sparse recovery is among the most well-studied problems in learning theory and high-dimensional statistics. In this work, we investigate the s
arXiv:2606.21366v2 Announce Type: replace-cross Abstract: This work examines sexualised AI-generated English-speaking voices offered by a popular commercial platform. New technologies may enable sexua
arXiv:2606.24038v1 Announce Type: new Abstract: This note describes an integration of the sim-to-real performance estimate with betting (from Chen et al.) and the safe anytime-valid inference (from Ra
arXiv:2606.24350v1 Announce Type: new Abstract: Legged robots rely on accurate ground interaction awareness to traverse variable terrains, such as slippery surfaces. Existing slip detection methods of
arXiv:2606.24847v1 Announce Type: new Abstract: Omnidirectional stereo images provide full-surround perception but violate the geometric assumptions of classical disparity estimation: in spherical or
arXiv:2507.09839v2 Announce Type: replace Abstract: An increasing number of NLP applications interact with large language models (LLMs) through black-box APIs, making prompt engineering critical for c
arXiv:2602.09303v2 Announce Type: replace Abstract: We propose a physics-informed consistency modeling framework for solving partial differential equations (PDEs) via fast, few-step generative inferen
arXiv:2606.17165v3 Announce Type: replace-cross Abstract: Organizations and researchers show increasing interest in using large language models (LLMs) in place of human participants in A/B tests, in t
arXiv:2606.23944v1 Announce Type: cross Abstract: State--space models provide a flexible framework for analyzing dynamical systems, yet they often rely on Gaussian assumptions that fail to capture hea
The common cold comes for us all—often more than once a year. And there is no way to prevent it. The best you can do is take vitamin C and stay away from people with the sniffles. Now the payment comp
arXiv:2111.05385v3 Announce Type: replace Abstract: Obesity is a major health problem, increasing the risk of various major chronic diseases, such as diabetes, cancer, and stroke. While the role of ob
arXiv:2606.24448v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models require large-scale video-action pairs, yet real teleoperation remains scarce. While generated robot videos offer a
arXiv:2502.01015v5 Announce Type: replace Abstract: Task arithmetic, representing downstream tasks through linear operations on task vectors, has emerged as a simple yet powerful paradigm for transfer
arXiv:2606.18074v2 Announce Type: replace-cross Abstract: Causal discovery seeks to uncover the causal dependencies among variables. For this purpose, we propose an algorithm called Tensor-based Secon
Thank you all for the overwhelming interest in our new Member of Technical Staff (RSI Lab) role. Just to clarify many questions asked, the role is not remote. We expect candidates to move to Tokyo, Ja
Edge cases and failure modes reveal the fundamental boundaries and constraints of complex systems more effectively than typical operations, making them valuable for understanding system behavior and l
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Introducing: the Engineering issue We can’t fix everything, bu
AI is booming. New use cases are emerging each day. To capitalize on the technology’s potential, enterprises require data at scale. In many cases, though, the relevant information is blocked or unstru
arXiv:2606.24191v1 Announce Type: new Abstract: Task specialization can improve the efficiency of multi-robot systems (MRSs). Previous works have investigated the emergence of task-specialist robot co
arXiv:2606.24157v1 Announce Type: new Abstract: The space P_2(R^d) of probability measures with finite second moment carries a natural geometry: the quadratic Wasserstein distance W_2 makes it a compl
arXiv:2601.18747v2 Announce Type: replace-cross Abstract: Modern AI agents increasingly rely on search infrastructure to execute complex, neuro-symbolic reasoning workflows. These workflows often comp
arXiv:2606.23853v1 Announce Type: cross Abstract: This paper studies strict majority reasoning in finite electorates using so-called extit{social decision frames}: finite sets of voters equipped with
The most complex phenomena arise from scalable recombination of very simple rules. Whether it's galaxies, chips, or neural networks, if you find the right primitive building blocks, the complexity tak
arXiv:2606.23897v1 Announce Type: cross Abstract: Prompt distillation compresses large vision-language models (VLMs) such as CLIP into lightweight student models by matching teacher predictions on unl
arXiv:2606.24627v1 Announce Type: new Abstract: Fact-checking systems built on LLMs achieve high verdict accuracy on standard benchmarks, yet routinely output Supports labels whose cited evidence does
As soon as August, a giant silver bullet will cut its way through the dry air of the southwestern US and cross the Pacific to reach the coast of Japan. Once there, the roughly 200-foot-long craft, bui
arXiv:2606.24074v1 Announce Type: cross Abstract: Wang~ite{Wang2026} introduced the Stochastic-Oracle Turing Machine (SOTM) framework and defined token complexity as the minimum expected cost of inter