Knowledge catalogue
arXiv:2604.21016v1 Announce Type: cross Abstract: When training neural networks with full-batch gradient descent (GD) and step size eta, the largest eigenvalue of the Hessian -- the sharpness S(oldsym
arXiv:2604.20937v1 Announce Type: new Abstract: Video Large Language Models (Video LLMs) incur high inference latency due to a large number of visual tokens provided to LLMs. To address this, training
arXiv:2604.21139v1 Announce Type: new Abstract: Language models must bind entities to the attributes they possess and maintain several such binding relationships within a context. We study how multipl
arXiv:2603.15055v2 Announce Type: replace-cross Abstract: We present a theory-guided generalized Bayesian methodology for spatio-temporal raster data, which we use to train an ensemble of stochastic f
arXiv:2604.20887v1 Announce Type: cross Abstract: The spectral kernel field equation R[k] = T[k] lacks a conservation-law analog. We prove (i) the fixed-point flow is strictly volume-expanding (tr DF
arXiv:2604.20849v1 Announce Type: cross Abstract: Retrieval-augmented generation over semi-structured sources such as HTML is constrained by a mismatch between document structure and the flat, sequenc
arXiv:2601.09056v3 Announce Type: replace-cross Abstract: Stylometry--the identification of an author through analysis of a text's style (i.e., authorship attribution)--serves many constructive purpos
arXiv:2604.21748v1 Announce Type: cross Abstract: Long-term conversational agents need memory systems that capture relationships between events, not merely isolated facts, to support temporal reasonin
arXiv:2604.21335v1 Announce Type: cross Abstract: Sub-token routing offers a finer control axis for transformer efficiency than the coarse units used in most prior work, such as tokens, pages, heads,
arXiv:2604.21172v1 Announce Type: cross Abstract: This paper develops a refined version of TAPO-description logic for the analysis of information behavior. The framework is treated not as a single hom
arXiv:2604.20891v1 Announce Type: cross Abstract: Memristive crossbars store numerical weights needing aggregation and decoding; a single junction means nothing alone. This paper presents a fundamenta
Nous Research announced that Kimi_Moonshot contributed an additional $1000 to a prize pool in celebration of the Kimi 2.6 release. This sponsorship gesture increased the total available prizes for wha
arXiv:2604.21537v1 Announce Type: new Abstract: Identifying critical nodes in complex networks is a fundamental task in graph mining. Yet, methods addressing an all-or-nothing coverage mechanics in a
arXiv:2604.21923v1 Announce Type: new Abstract: We study the minimax sample complexity of multicalibration in the batch setting. A learner observes n i.i.d. samples from an unknown distribution and mu
The web is disappearing 🕳️ According to a Pew Research Center report, 26% of pages from 2013-2023 are no longer accessible. But that’s not the whole story. In a new study published in Internet Archive
arXiv:2604.21691v1 Announce Type: cross Abstract: In this paper, we make the case that a scientific theory of deep learning is emerging. By this we mean a theory which characterizes important properti
arXiv:2604.21057v1 Announce Type: new Abstract: The field of Language Reasoning Models (LRMs) has been very active over the past few years with advances in training and inference techniques enabling L
arXiv:2604.21657v1 Announce Type: new Abstract: Machine learning methods that predict initial guesses from molecular geometry can reduce this cost, but matrix-prediction models fail when extrapolating
arXiv:2511.03232v2 Announce Type: replace Abstract: Recently, Mamba-based super-resolution (SR) methods have demonstrated the ability to capture global receptive fields with linear complexity, address
arXiv:2512.03465v3 Announce Type: replace-cross Abstract: In this study, we more rigorously evaluated our attack script extit{TraceTarnish}, which leverages adversarial stylometry principles to anonym
arXiv:2604.21227v1 Announce Type: new Abstract: Facial action unit (AU) detection remains challenging because it involves heterogeneous, AU-specific uncertainties arising at both the representation an
arXiv:2512.20288v2 Announce Type: replace-cross Abstract: Recent advances in deep learning have led to its widespread adoption across diverse domains, including medical imaging. This progress is drive
arXiv:2604.21534v1 Announce Type: new Abstract: This paper presents our system developed for SemEval-2026 Task 2. The task requires modeling both current affect and short-term affective change in chro
arXiv:2604.21238v1 Announce Type: new Abstract: Multi-table entity matching (MEM) addresses the limitations of dual-table approaches by enabling simultaneous identification of equivalent entities acro
arXiv:2604.20925v1 Announce Type: new Abstract: While current deep learning models achieve high performance by learning statistical correlations from vast datasets,which stands in stark contrast to hu
arXiv:2604.21603v1 Announce Type: cross Abstract: We explore the use of answer set programming (ASP) and its extension with quantifiers, ASP(Q), for inconsistency-tolerant querying of prioritized data
arXiv:2604.20921v1 Announce Type: new Abstract: We evaluated whether a glaucoma risk assessment (GRA) model trained on All of Us national data can identify patients at high probability of glaucoma usi
arXiv:2604.21599v1 Announce Type: cross Abstract: Machine Learning (ML) Engineering is a growing field that necessitates an increase in the rigor of ML development. It draws many ideas from software e
arXiv:2511.13587v2 Announce Type: replace-cross Abstract: Visual autoregressive (AR) generation models have demonstrated strong potential for image generation, yet their next-token-prediction paradigm
arXiv:2604.20897v1 Announce Type: cross Abstract: We develop a thermodynamic theory of algorithmic catalysis within the watts-per-intelligence framework, identifying reusable computational structures
arXiv:2502.10600v4 Announce Type: replace-cross Abstract: Approximating a probability distribution using a set of particles is a fundamental problem in machine learning and statistics, with applicatio
arXiv:2604.21082v1 Announce Type: new Abstract: Training vision-language models (VLMs) for medical report generation is often hindered by the scarcity of high-quality annotated data. This work evaluat
arXiv:2602.00469v2 Announce Type: replace-cross Abstract: While word embeddings derive meaning from co-occurrence patterns, human language understanding is grounded in sensory and motor experience. We
arXiv:2604.05260v2 Announce Type: replace Abstract: There is a growing need for robots that can change their shape, size and mechanical properties to adapt to evolving tasks and environments. However,
arXiv:2604.05687v2 Announce Type: replace Abstract: Reconstructing 3D scenes from smoke-degraded multi-view images is particularly difficult because smoke introduces strong scattering effects, view-de
arXiv:2604.19995v1 Announce Type: new Abstract: The contemporary media landscape is characterized by sensational short videos. While prior research examines the effects of individual multimodal featur
arXiv:2604.20692v1 Announce Type: new Abstract: Evaluating the pinch capability of a robotic hand is important for understanding its functional dexterity. However, many existing grasp evaluation metho
IBM Research has developed an AI model designed to analyze and predict the behavior of fusion plasma, advancing computational capabilities for nuclear fusion research. The model likely leverages machi
arXiv:2507.07800v3 Announce Type: replace-cross Abstract: Segmenting cytoskeletal filaments in microscopy images is essential for studying their roles in cellular processes. However, this task is high
arXiv:2510.08465v2 Announce Type: replace-cross Abstract: Estimating how individual input variables affect the output of a black-box model is a central task in explainable machine learning. However, e
arXiv:2604.20204v1 Announce Type: new Abstract: Cross-sectional stock ranking is a fundamental task in quantitative investment, relying on both temporal modeling of individual stocks and the capture o
Actually, AI already saves lives. In several countries, mammograms are examined by AI and radiologists. Reliability is improved. In the EU, every car sold must be equipped with Automatic Emergency Bra
arXiv:2507.16433v2 Announce Type: replace-cross Abstract: Accurate transfer of information across multiple sectors to enhance model estimation is both significant and challenging in multi-sector portf
arXiv:2604.20135v1 Announce Type: new Abstract: Multimodal representation is crucial for E-commerce tasks such as identical product retrieval. Large representation models (e.g., VLM2Vec) demonstrate s
arXiv:2601.23258v2 Announce Type: replace-cross Abstract: Recent works on language identification and generation have established tight statistical rates at which these tasks can be achieved. These wo
arXiv:2604.20721v1 Announce Type: new Abstract: Long-Horizon (LH) tasks in Human-Scene Interaction (HSI) are complex multi-step tasks that require continuous planning, sequential decision-making, and
arXiv:2604.19753v1 Announce Type: new Abstract: We propose a feature-free approach to algorithm selection that replaces hand-crafted instance features with pretrained text embeddings. Our method, Zero
arXiv:2604.20535v1 Announce Type: new Abstract: Atypical speech is receiving greater attention in speech technology research, but much of this work unfolds with limited interdisciplinary dialogue. For
arXiv:2604.20077v1 Announce Type: new Abstract: Large-scale kernel ridge regression (KRR) is limited by the need to store a large kernel matrix K_t. To avoid storing the entire matrix K_t, Nystrom met
arXiv:2602.00208v2 Announce Type: replace-cross Abstract: Unsupervised anomaly detection is a challenging problem due to the diversity of data distributions and the lack of labels. Ensemble methods ar
arXiv:2511.19367v2 Announce Type: replace-cross Abstract: Accurate tumor staging in lung cancer is crucial for prognosis and treatment planning and is governed by explicit anatomical criteria under fi
arXiv:2604.20263v1 Announce Type: cross Abstract: Virtual cell modeling predicts molecular state changes under genetic perturbations in silico, which is essential for biological mechanism studies. How
arXiv:2603.17478v2 Announce Type: replace-cross Abstract: This study explores the combination of automated machine learning (AutoML) with model-based deep unfolding (DU) for optimizing wireless beamfo
arXiv:2511.17113v2 Announce Type: replace-cross Abstract: Network Intrusion Detection Systems (NIDS) are essential tools for detecting network attacks and intrusions. While extensive research has expl
arXiv:2403.18151v2 Announce Type: replace-cross Abstract: Objective: Cytology plays a crucial role in lung cancer diagnosis. Pulmonary cytology involves cell morphological characterization in the spec
arXiv:2509.25844v3 Announce Type: replace Abstract: When people query Vision-Language Models (VLMs) but cannot see the accompanying visual context (e.g. for blind and low-vision users), augmenting VLM
arXiv:2604.20606v1 Announce Type: cross Abstract: Vision Mamba, as a state space model (SSM), employs a zero-order hold (ZOH) discretization, which assumes that input signals remain constant between s
BIG PERSONAL UPDATE. I've joined a16z as a partner investing in infra and AI. I'm also stepping down as CEO of Rosebud AI. I reflect in this article on my 8 years of building in generative AI. At @a16
arXiv:2604.20243v1 Announce Type: new Abstract: Color constancy is a fundamental ability of many biological visual systems and a crucial step in computer imaging systems. Bio-inspired modeling offers
Build your own harness, folks. You won't regret it. These days, you just have to fix things yourself. It's doable, and it will set you up to easily deal with some of the madness that's happening in th