Knowledge catalogue
arXiv:2604.25316v1 Announce Type: new Abstract: Domain adaptation (DA) addresses the challenge of transferring a machine learning model trained on a source domain to a target domain with a different d
arXiv:2604.24878v1 Announce Type: new Abstract: We provide a systematic recipe for translating ReLU approximation results to softmax attention mechanism. This recipe covers many common approximation t
Trump’s FCC chair, Brendan Carr, says he plans to punish and potentially revoke broadcast licenses for TV networks critical of the Trump administration: “I’d be surprised if we don’t go down the path
arXiv:2604.24883v1 Announce Type: cross Abstract: We study the zero-temperature phase diagram of the 2D spin-imbalanced Fermi gas with short-ranged attractive interactions using the recently developed
arXiv:2410.09635v2 Announce Type: replace Abstract: Early detection of intrapartum risks enables timely interventions to prevent or mitigate adverse labor outcomes such as cerebral palsy. However, acc
arXiv:2409.11063v3 Announce Type: replace-cross Abstract: Variational principles play a central role in classical mechanics, providing compact formulations of dynamics and direct access to conserved q
arXiv:2604.25570v1 Announce Type: new Abstract: Spiking Transformers have shown strong potential for long-range visual modeling through spike-driven self-attention. However, their quadratic token inte
arXiv:2512.12072v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly being used to generate synthetic datasets for the evaluation and training of downstream models. Howeve
arXiv:2604.25132v1 Announce Type: new Abstract: Instruction-tuning datasets often contain substantial redundancy and low-quality samples, necessitating effective data selection methods. We propose an
arXiv:2603.14248v2 Announce Type: replace-cross Abstract: Large language model (LLM) web agents are increasingly used for web navigation but remain far from human reliability on realistic, long-horizo
arXiv:2604.25011v1 Announce Type: new Abstract: Reinforcement learning (RL)-based post-training often improves the reasoning performance of large language models (LLMs) beyond the training domain, whi
arXiv:2604.25384v1 Announce Type: new Abstract: This paper presents a methodology for transforming raw Wikimedia dumps into quality textual corpora for seven South Slavic languages. The work is divide
arXiv:2604.24172v1 Announce Type: cross Abstract: This paper uses a minimum divergence framework to introduce a new way of calculating model weights that can be used to average probabilistic predictio
arXiv:2604.24672v1 Announce Type: new Abstract: We provide a mathematical interpretation of convolutional (or message passing) neural networks by using presheaves and copresheaves of the set of contin
arXiv:2604.23415v1 Announce Type: new Abstract: Most two-stream action recognition networks apply the same convolutional backbone to both RGB and optical flow streams, ignoring the fact that the two m
arXiv:2604.22864v1 Announce Type: cross Abstract: Existing benchmarks for systematic reviewing remain limited either in scale or in disciplinary coverage, with some collections comprising only a modes
arXiv:2604.23225v1 Announce Type: new Abstract: This paper investigates the deep learning optimization problem with softmax cross-entropy loss. We propose a layer separation strategy to alleviate the
arXiv:2507.16079v2 Announce Type: replace-cross Abstract: With the advancement of deep learning, reducing computational complexity and memory consumption has become a critical challenge, and ternary n
arXiv:2604.23468v1 Announce Type: cross Abstract: In 2016, Viazovska famously solved the sphere packing problem in dimension 8, using modular forms to construct a 'magic' function satisfying optimalit
arXiv:2507.22345v2 Announce Type: replace Abstract: Wheel-legged robots integrate leg agility on rough terrain with wheel efficiency on flat ground. However, most existing designs do not fully capital
arXiv:2604.22877v1 Announce Type: cross Abstract: GBM is a highly aggressive primary malignancy in adults, necessitating personalized therapeutic strategies due to its inherent molecular heterogeneity
arXiv:2604.24468v1 Announce Type: cross Abstract: Fine-tuning unlocks large language models (LLMs) for specialized applications, but its high computational cost often puts it out of reach for resource
arXiv:2604.23622v1 Announce Type: new Abstract: In the hyperspectral image (HSI) classification task, each pixel is categorized into a specific land-cover category or material. Convolutional neural ne
arXiv:2604.23114v1 Announce Type: new Abstract: In limited-data settings, a single endpoint mean of an evaluation metric such as the Continuous Ranked Probability Score (CRPS) is itself a random varia
arXiv:2604.23167v1 Announce Type: new Abstract: A levelset free but a hybrid image segmentation approach based on a modified version of the piece wise constant shape gradient of an Mumford Shah shape
arXiv:2604.23184v1 Announce Type: cross Abstract: We propose a unified fractional regularization framework for sparse signal recovery based on the ell_1/ell_p^q model. Our main theoretical contributio
arXiv:2604.24043v1 Announce Type: new Abstract: Designing heuristics for combinatorial optimization problems (COPs) is a fundamental yet challenging task that traditionally requires extensive domain e
arXiv:2510.23215v2 Announce Type: replace-cross Abstract: Eigenvalue problems are among the most important topics in many scientific disciplines. With the recent surge and development of machine learn
arXiv:2604.22901v1 Announce Type: new Abstract: Diffusion models achieve remarkable success in time series generation. However, slow inference limits their practical deployment. We propose E^2-CRF (Er
arXiv:2604.22850v1 Announce Type: new Abstract: Industrial visual inspection systems often suffer from a severe scarcity of labeled defect data, particularly during the early stages of New Product Int
The ACL Rolling Review (ARR) operates on a two-monthly review cycle , and the March 2026 cycle refers to one of these periodic submission and peer review rounds for computational linguistics research.
arXiv:2604.24407v1 Announce Type: new Abstract: The recent surge in content consumption through streaming services has driven a growing demand for personalized content. Personalized advertisements (ad
arXiv:2409.01579v2 Announce Type: replace-cross Abstract: Retrieved documents containing noise will hinder RAG from detecting answer clues and make the inference process slow and expensive. Therefore,
arXiv:2604.24175v1 Announce Type: cross Abstract: Large language models have demonstrated strong reasoning capabilities in general knowledge question answering. However, their ability to handle tempor
arXiv:2604.24474v1 Announce Type: new Abstract: Molecular similarity plays a central role in ligand-based drug discovery, such as virtual screening, analog searching, and goal-directed molecular gener
arXiv:2407.05595v3 Announce Type: replace Abstract: Medical palpation is more than force transmission. It is a bidirectional cognitive and emotional exchange between doctor and patient. We model two c
arXiv:2505.19763v3 Announce Type: replace Abstract: The seminal breakthrough of AlphaFold in protein structure prediction relied on a learned potential energy function parameterized by deep models, in
arXiv:2505.01595v2 Announce Type: replace-cross Abstract: We present a state-of-the-art model for fine-grained probability estimation of propositions conditioned on context. Recent advances in large l
arXiv:2604.24331v1 Announce Type: new Abstract: Research on video-based eye-tracking has long explored stereo and glint-based methods, yet existing wearable eye trackers - both commercial and open-sou
arXiv:2604.23666v1 Announce Type: cross Abstract: Line current differential relays (LCDRs) are measurement-driven relays that rely on time-synchronized multi-phase current waveforms to infer internal
arXiv:2604.22777v1 Announce Type: new Abstract: Fault diagnosis of general aviation aircraft faces challenges including scarce real fault data, diverse fault types, and weak fault signatures. This pap
arXiv:2512.09972v5 Announce Type: replace-cross Abstract: Navigating the capability--efficiency trade-off in Large Language Models (LLMs) requires approximating a high-quality Pareto set. Existing mod
arXiv:2604.22816v1 Announce Type: cross Abstract: AI-enhanced interference rejection in radio frequency (RF) transmissions has recently attracted interest because deep learning approaches trained on b
arXiv:2604.23418v1 Announce Type: new Abstract: Uniform random rotations are a useful primitive in applications such as fast Johnson-Lindenstrauss embeddings, kernel approximation, communication-effic
ARC Prize 2026: ARC-AGI-3 now has H100s Thank you to our partners at @kaggle for powering the ARC-AGI-3 competition with H100s Participants now have a pool of accelerators (subject to submission limit
arXiv:2604.23430v1 Announce Type: cross Abstract: The relentless expansion of scientific literature presents significant challenges for navigation and knowledge discovery. Within Research Information
arXiv:2604.24685v1 Announce Type: new Abstract: Chromosome analysis is a fundamental step in the diagnosis of genetic diseases, but the manual karyotyping workflow is time-consuming and heavily depend
arXiv:2601.06166v2 Announce Type: replace Abstract: Accelerated dynamic volumetric magnetic resonance imaging (4DMRI) is essential for applications relying on motion resolution. Existing 4DMRI produce
arXiv:2512.07868v2 Announce Type: replace-cross Abstract: Bayesian optimization is widely used for optimizing expensive black box functions, but most existing approaches focus on scalar responses. In
arXiv:2511.20006v2 Announce Type: replace-cross Abstract: Automatic Pitch Correction (APC) enhances vocal recordings by aligning pitch deviations with intended musical notes. However, existing APC sys
arXiv:2506.22429v2 Announce Type: replace-cross Abstract: In recent years, the neural tangent kernel (NTK) and neural network Gaussian process kernel (NNGP) have given theoreticians tractable limiting
arXiv:2604.24089v1 Announce Type: new Abstract: Bridging molecular structures and natural language is essential for controllable design. Autoregressive models struggle with long-range dependencies, wh
arXiv:2604.24311v1 Announce Type: new Abstract: Automatic generation of Building Information Models (BIM) from building scans is a key challenge in architecture and construction. We present a modular
arXiv:2511.09465v3 Announce Type: replace-cross Abstract: Diffusion and flow matching approaches to generative modeling have shown promise in domains where the state space is continuous, such as image
arXiv:2604.24024v1 Announce Type: new Abstract: Conventional multi-projector calibration requires projecting and capturing structured light patterns for each projector sequentially, causing calibratio
arXiv:2604.22984v1 Announce Type: new Abstract: We train a language model to generate LEGO-brick build sequences. While prior work has been restricted to discrete, voxel-like towers, we consider a muc
arXiv:2510.13799v2 Announce Type: replace Abstract: As retrieval-augmented generation (RAG) tackles complex tasks, increasingly expanded contexts offer richer information, but at the cost of higher la
arXiv:2604.23803v1 Announce Type: new Abstract: Egocentric video provides a unique view into human perception and interaction, with growing relevance for augmented reality, robotics, and assistive tec
arXiv:2604.23165v1 Announce Type: new Abstract: Spiking Vision Transformers (S-ViTs) offer a promising framework for energy-efficient visual learning. However, existing designs remain limited by two f
arXiv:2604.23508v1 Announce Type: new Abstract: Burst image super resolution (BISR) aims to construct a single high-resolution (HR) image by aggregating information from multiple low-resolution (LR) f