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arXiv:2604.17669v1 Announce Type: new Abstract: This paper presents a comprehensive review of the NTIRE 2026 Low Light Image Enhancement Challenge, highlighting the proposed solutions and final result

arXiv:2509.11983v2 Announce Type: replace Abstract: Neural network (NN) training is inherently a large-scale matrix optimization problem, yet the matrix structure of NN parameters has long been overlo

arXiv:2604.16620v1 Announce Type: new Abstract: Analysis of Stochastic Gradient Descent (SGD) and its variants typically relies on the assumption of uniformly bounded variance, a condition that freque

arXiv:2604.18490v1 Announce Type: new Abstract: Existing MT evaluation frameworks, including automatic metrics and human evaluation schemes such as Multidimensional Quality Metrics (MQM), are largely

arXiv:2506.13743v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems typically rely on a single fixed retriever, despite growing evidence that no single retriever performs

LTX 2.3 GGUF 12GB is an updated workflow tool for image generation that now supports multi-image input functionality, with pre-configured workflows for first-frame-last-frame (FFLF) processing using u

arXiv:2604.17976v1 Announce Type: new Abstract: This paper presents ltzGLUE, the first Natural Language Understanding (NLU) benchmark for Luxembourgish (LTZ) based on the popular GLUE benchmark for En

arXiv:2511.09818v2 Announce Type: replace Abstract: Restoring 3D scenes with low-light conditions is challenging, and most existing methods depend on precomputed camera poses and scene-specific optimi

arXiv:2601.19792v3 Announce Type: replace Abstract: For generative AI agents to partner effectively with human users, the ability to accurately predict human intent is critical. But this ability to co

Lyft built 8 agents that resolve 35% of customer issues end-to-end. That stat sounds crazy, but it's the kind of numbers you see when teams actually close the evals feedback loop. Looking forward to I

arXiv:2604.17862v1 Announce Type: new Abstract: As deep learning-based AI technologies gain momentum, the demand for general-purpose AI computing architectures continues to grow. While GPGPU-based arc

arXiv:2602.10732v2 Announce Type: replace Abstract: Multilingual benchmarks rarely test reasoning over culturally grounded premises: translated datasets keep English-centric scenarios, while culture-f

arXiv:2407.09514v3 Announce Type: replace-cross Abstract: Recently, metal-organic frameworks (MOFs) have demonstrated their potential as solid-state electrolytes in proton exchange membrane fuel cells

arXiv:2604.17470v1 Announce Type: new Abstract: Machine learning has become a powerful tool for discovering governing laws of dynamical systems from data. However, most existing approaches degrade sev

OpenAI's ChatGPT Images 2.0 represents an updated version of the image generation capabilities within ChatGPT, likely featuring improved quality, faster generation times, or enhanced creative control

arXiv:2604.16588v1 Announce Type: new Abstract: Penalty kicks in soccer are decided under extreme time constraints, where goalkeepers benefit from anticipating shot direction from the kickers motion b

arXiv:2512.00198v2 Announce Type: replace Abstract: Breast cancer is one of the leading causes of death among women worldwide. We introduce Mammo-FM, the first foundation model specifically for mammog

Many folks seem to be confused, and think the collapse of the CS major graduation numbers at Berkeley could be linked to the 'AI is taking SWE jobs' hysteria narrative. Here's the easiest way to see t

arXiv:2604.17569v1 Announce Type: new Abstract: Automated Essay Scoring (AES) faces significant challenges in cross-prompt settings, where models must generalize to unseen writing prompts. To address

arXiv:2604.16765v1 Announce Type: cross Abstract: Online political hostility is pervasive, yet it remains unclear how toxicity varies across campaign issues and political ideology, and what psychosoci

arXiv:2604.16313v1 Announce Type: cross Abstract: Retrieval-based multimodal document QA aims to identify and integrate relevant information from visually rich documents with complex multimodal struct

arXiv:2604.18267v1 Announce Type: new Abstract: Recent advances in semantic correspondence rely on dual-encoder architectures, combining DINOv2 with diffusion backbones. While accurate, these billion-

Mark Zuckerberg and Meta Platforms $META just sent a memo to employees saying Meta Platforms is installing a new tracking software on the computers of all employees in the United States 🇺🇸 so it can t

arXiv:2604.17090v1 Announce Type: new Abstract: Human action recognition and motion generation are two active research problems in human-centric computer vision, both aiming to align motion with textu

arXiv:2602.17550v3 Announce Type: replace Abstract: Existing Reinforcement Learning with Verifiable Rewards (RLVR) algorithms, such as GRPO, rely on rigid, uniform, and symmetric trust region mechanis

arXiv:2604.18509v1 Announce Type: new Abstract: Large language models (LLMs) are widely used in retrieval-augmented generation (RAG) to incorporate external knowledge at inference time. However, when

MASSIVE: 🇺🇸 The BBC just validated everything we've been saying. A clear pattern of trades right before major Trump announcements. Iran war. Tariff reversals. Policy shifts. We tracked a whale for wee

This live broadcast on Replit's X account demonstrates how to work with databases within the Replit development environment, covering practical techniques for database integration and management. The

This DigitalOcean guide covers strategies and best practices for deploying and optimizing very large language models (600 billion+ parameters) on cloud infrastructure, focusing on inference performanc

arXiv:2604.16410v1 Announce Type: new Abstract: CLIP adaptation can improve in-domain accuracy while degrading out-of-domain transfer, but comparisons between Full Fine-Tuning (Full FT) and LoRA are o

arXiv:2503.16549v2 Announce Type: replace Abstract: Despite strong results on many tasks, multimodal large language models (MLLMs) still underperform on visual mathematical problem solving, especially

arXiv:2604.18584v1 Announce Type: cross Abstract: Mathematical problem solving remains a challenging test of reasoning for large language and multimodal models, yet existing benchmarks are limited in

arXiv:2604.17484v1 Announce Type: cross Abstract: Retrieving mathematical knowledge is a central task in both human-driven research, such as determining whether a result already exists, finding relate

arXiv:2511.21686v2 Announce Type: replace Abstract: Synthetic data has become increasingly important for training large language models, especially when real data is scarce, expensive, or privacy-sens

arXiv:2601.03190v3 Announce Type: replace Abstract: Machine unlearning aims to forget sensitive knowledge from Large Language Models (LLMs) while maintaining general utility. However, existing approac

arXiv:2604.16929v1 Announce Type: new Abstract: The accurate extraction of scientific measurements from literature is a critical yet challenging task in AI4Science, enabling large-scale analysis and i

arXiv:2604.17650v1 Announce Type: new Abstract: LLMs are increasingly deployed in dynamic, real-world settings, where the distribution of user prompts can shift substantially over time as new tasks, p

arXiv:2604.16421v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated on mathematical reasoning, yet their robustness to equivalent problem representations remains po

arXiv:2601.06931v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly deployed in socially consequential settings, raising concerns about social bias driven by demog

arXiv:2604.16417v1 Announce Type: cross Abstract: This study examines the relationship between media coverage and public information demand during the Lebanon conflict in March 2026. Using a dataset o

arXiv:2411.17690v3 Announce Type: replace-cross Abstract: Unified decoder-only transformers have shown promise for multimodal generation, yet the mechanisms by which they synchronize modalities with h

arXiv:2604.16512v1 Announce Type: new Abstract: We propose a novel variational method to compute a highly accurate global signed distance function (SDF) to a given point cloud. To this end, the jump s

arXiv:2604.18250v1 Announce Type: new Abstract: Accurate prognostication and risk estimation are essential for guiding clinical decision-making and optimizing patient management. While radiologist-ass

arXiv:2604.16506v1 Announce Type: cross Abstract: Large language models perform well on many medical QA benchmarks, but real clinical reasoning often requires integrating evidence across multiple imag

arXiv:2604.17899v1 Announce Type: new Abstract: Unlike macro-expression, micro-expression does not follow a strictly consistent mapping rule between emotions and Action Units (AUs). As a result, some

arXiv:2604.17282v1 Announce Type: new Abstract: Process-Level Reward Models (PRMs) are essential for guiding complex reasoning in large language models, yet existing PRM benchmarks cover only general