Search: “model-releases”

Lost in the Tail: Addressing Geographic Imbalance in Urban Visual Place Recognition

arXiv:2607.00090v1 Announce Type: cross Abstract: Urban-scale Visual Place Recognition (VPR) aims to identify the geographic location of a query image by matching it against a geo-tagged database. Whi

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Model Releases

LUMA: Benchmarking Segmentation via a Lightweight Universal Mask Adapter

DGX agent

arXiv:2607.00687v1 Announce Type: cross Abstract: Comparing transformer backbones for image segmentation is confounded: each is paired with a different decoder, recipe, and pretraining, so reported di

model-releasesarxiv-cs-ai

2 Jul 2026

LuxIT: A Luxembourgish Instruction Tuning Dataset from Monolingual Seed Data

arXiv:2510.24434v3 Announce Type: replace Abstract: The effectiveness of instruction-tuned Large Language Models (LLMs) is often limited in low-resource linguistic settings due to a lack of high-quali

LV-ROVER: Multi-Stream Tesseract Voting for Maltese Paragraph OCR

arXiv:2607.00250v1 Announce Type: new Abstract: Maltese has decent text corpora and pretrained language models, but, like many languages outside the handful with large OCR benchmarks, only a single kn

Mapping the Evaluation Frontier: An Empirical Survey of the Bias-Reliability Tradeoff Across Eleven Evaluator-Agent Conditions

arXiv:2607.00304v1 Announce Type: cross Abstract: The bias-reliability tradeoff conjectures that LLM evaluation systems are constrained in (gamma, H, CV) space, where evaluator coupling (gamma), strat

Meet Vultr and Our AI Ecosystem Partners at RAISE Summit Paris 2026

Vultr will be participating in the RAISE Summit Paris 2026, showcasing their infrastructure and AI ecosystem partnerships at the event. The summit appears to be a major gathering focused on AI and rel

model-releasesvultr

MemSyco-Bench: Benchmarking Sycophancy in Agent Memory

arXiv:2607.01071v1 Announce Type: cross Abstract: Memory has emerged as a cornerstone of modern LLM-based agents, supporting their evolution from single-turn assistants to long-term collaborators. How

MEPA: Multi-Scale Representation Alignment for Visual Autoregressive Modeling with Mixture of Experts

arXiv:2607.00371v1 Announce Type: cross Abstract: Visual AutoRegressive modeling (VAR) has pioneered a coarse-to-fine multi-scale autoregressive generative paradigm, demonstrating strong capabilities

Microsoft launches AI-focused professional services business with $2.5B investment

model-releasessiliconangle

Microsoft Corp. has formed a new business that will help organizations build and manage artificial intelligence applications. The Microsoft Frontier Company, as the venture is called, launched today w

MindAU: EEG-Conditioned Facial Action Unit Editing via Dual-Stream Manifold Alignment

arXiv:2607.00410v1 Announce Type: new Abstract: Recent brain decoding studies have made substantial progress in reconstructing externally perceived visual content from neural signals. However, using e

MindEdit-Bench: Benchmarking Object-Level Counterfactual Spatial Reasoning in VLMs from In-the-Wild Photos

arXiv:2607.00491v1 Announce Type: cross Abstract: Benchmarks for vision-language models (VLMs) mostly test observational spatial reasoning: models describe relations already visible in the input. Exis

MMLoP: Multi-Modal Low-Rank Prompting for Efficient Vision-Language Adaptation

arXiv:2602.21397v2 Announce Type: replace Abstract: Prompt learning has become a dominant paradigm for adapting vision-language models (VLMs) such as CLIP to downstream tasks without modifying pretrai

MoHallBench: A Benchmark for Motion Hallucination in Video Large Language Models

arXiv:2607.01117v1 Announce Type: new Abstract: Video Large Language Models (VideoLLMs) have shown strong progress in video understanding, yet they still suffer from hallucinations that are inconsiste

MolSafeEval: A Benchmark for Uncovering Safety Risks in AI-Generated Molecules

arXiv:2607.00464v1 Announce Type: cross Abstract: Current molecular generation benchmarks emphasize task complexity, molecule novelty, and property alignment; they largely overlook a critical concern:

MSQA: A Natively Sourced Multilingual and Multicultural SimpleQA Benchmark

arXiv:2607.00724v1 Announce Type: new Abstract: Multilingual fluency often invites a stronger assumption: a model that can speak a user's language must also understand the culture encoded by that lang

Multi-Hypothesis Test-Time Adaptation to Mitigate Underspecification

arXiv:2607.00259v1 Announce Type: cross Abstract: Test-Time Adaptation (TTA) seeks to improve model robustness under distribution shifts by adapting parameters using unlabeled target data. However, in

Multi-Label Node Classification with Label Influence Propagation

arXiv:2607.00671v1 Announce Type: cross Abstract: Graphs are a complex and versatile data structure used across various domains, with possibly multi-label nodes playing a particularly crucial role. Ex

Multimodal Continuous Reasoning via Asymmetric Mutual Variational Learning

arXiv:2607.00461v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are often constrained by a language-space bottleneck, forcing complex visual reasoning into discrete tokens whi

MultiSynt/MT: Trillion-Token Multi-Parallel Pre-Training Data Translated Across 36 Languages

arXiv:2607.00890v1 Announce Type: new Abstract: Open web-scale pre-training corpora remain concentrated in English, limiting multilingual LLM development. We introduce MultiSynt/MT, an open synthetic

my fave question, talked about this coding agent Eval+Improvement loop infra + UX in my AIE talk yesterday! biased but LangSmith is the best…

model-releasesharrison-chase--x

my fave question, talked about this coding agent Eval+Improvement loop infra + UX in my AIE talk yesterday! biased but LangSmith is the best spot to Eval + continuously improve your coding agents, and

Neural Network-Based Estimation of Time-Dependent Parameters in AR(p) Processes

arXiv:2607.00470v1 Announce Type: cross Abstract: We investigate a forecasting framework based on a simple discrete-time dynamic model with coefficients varying in time. The parameters of the model ar

Next-Frame Decoding for Ultra-Low-Bitrate Image Compression with Video Diffusion Priors

arXiv:2603.15129v3 Announce Type: replace Abstract: We present a novel paradigm for ultra-low-bitrate image compression (ULB-IC) that exploits the ``temporal'' evolution in generative image compressio

Not All Prediction Targets Keep Training-Free Diffusion Guidance on the Manifold

arXiv:2607.00647v1 Announce Type: new Abstract: Training-free guidance (TFG) steers a pretrained diffusion model toward a desired attribute at inference. To be effective, this guidance must be applied

OmniFall: From Staged Through Synthetic to Wild, A Unified Multi-Domain Dataset for Robust Fall Detection

arXiv:2505.19889v3 Announce Type: replace Abstract: Visual fall detection models are usually trained on small, staged datasets. Their real-world utility remains unclear; such data lacks diversity and

OmniMoE: An Efficient MoE by Orchestrating Atomic Experts at Scale

arXiv:2602.05711v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) architectures are evolving towards finer granularity to improve parameter efficiency. However, existing MoE designs f

On the Reliability of Cue Conflict and Beyond

arXiv:2603.10834v4 Announce Type: replace-cross Abstract: Understanding how neural networks rely on visual cues offers a human-interpretable view of their internal decision processes. The cue-conflict

OSCAR: Occupancy-based Shape Completion via Acoustic Neural Implicit Representations

arXiv:2603.08279v2 Announce Type: replace Abstract: Accurate 3D reconstruction of vertebral anatomy from ultrasound is important for guiding minimally invasive spine interventions, but it remains chal

Pano2World: End-to-End 3D Generation via Unified Multi-View Sequences

arXiv:2607.00832v1 Announce Type: cross Abstract: A single panorama captures the full visual sphere from one camera center, yet confines users to looking around in place without enabling true scene ex

Persona Without Substrate: Regime-Dependence and the LLM Individuation Problem

arXiv:2607.00006v1 Announce Type: cross Abstract: Beckmann & Butlin's (2026) ontological framework for the LLM individuation problem inherits an unargued cross-regime co-reference assumption from the

PHREEQC-MCQ-200: A Diagnostic Benchmark for Tool-Augmented Scientific Simulator Agents

arXiv:2607.00436v1 Announce Type: new Abstract: Large language model agents are increasingly connected to scientific software, yet it remains unclear when tool access makes scientific computation more

PixelEyes: Decoupling Perception and Reasoning for Pinpoint Visual Evidence Seeking

arXiv:2607.00115v1 Announce Type: new Abstract: This paper explores multi-turn visual reasoning and observes that MLLMs repeatedly fail to localize the target, leading to long, redundant trajectories.

PorTEXTO: A European Portuguese Benchmark for Visual Text Extraction

arXiv:2606.19096v2 Announce Type: replace Abstract: European Portuguese (pt-PT) is largely absent from OCR benchmarks, which skew toward high-resource languages. The few benchmarks that cover pt-PT fo

Post-Training Pruning for Diffusion Transformers

arXiv:2607.00927v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) have demonstrated impressive performance in image generation but suffer from substantial computational overhead and reso

Prompting GPT-5 on Scrum Certification Questions: An Empirical Accuracy Study

arXiv:2607.00049v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in Agile Software Development for documentation, coaching, and training. As practitioners adopt the

QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks

arXiv:2607.00974v1 Announce Type: cross Abstract: Static radio maps provide location-dependent propagation priors, but they cannot capture short-term blockage caused by moving objects. Direct sensing-

Quantifying the Affective Gap: A Zero-Shot Evaluation of LLMs on Fine-Grained Emotion Taxonomies

arXiv:2607.00968v1 Announce Type: new Abstract: Emotion recognition in natural language is a foundational challenge in affective computing, with critical implications for human-computer interaction, m

Quantum vs. Classical Machine Learning: A Unified Empirical Comparison

arXiv:2607.01197v1 Announce Type: new Abstract: Quantum computing has emerged as a promising computational paradigm for machine learning (ML), with the potential to offer computational advantages over

Radial Interaction Tomography: Recognizing Non-Transitive Evolutionary Games from One Range-Expansion Image

arXiv:2607.00378v1 Announce Type: new Abstract: Colored sectors in a microbial range expansion encode more than lineage survival counts. We formulate a computer-vision inverse problem: from one endpoi

Rampart, our PII removal model, has cracked the first screen of the top trending models across any category on Huggingface, on the same tier…

model-releasesclem-delangue--x

Rampart, our PII removal model, has cracked the first screen of the top trending models across any category on Huggingface, on the same tier as GLM 5.2 / Deepseek! If building systems at fast pace at

RC-GeoCP: Geometric Consensus for Radar-Camera Collaborative Perception

arXiv:2603.00654v3 Announce Type: replace Abstract: Collaborative perception (CP) improves scene understanding through multi-agent information sharing, yet LiDAR-centric systems remain costly and vuln

Recovering Input Text from Hidden States: Study of Gradient-Based Inversion of Decoder-Only Language Models

arXiv:2607.00852v1 Announce Type: cross Abstract: This work studies the hidden-state inversion problem: recovering the original input token sequence of a decoder-only language model from its last-laye

RetailSMV: Exocentric vs. Egocentric Adaptation of Foundation Video World Models in Retail

arXiv:2607.00310v1 Announce Type: cross Abstract: Foundation video diffusion models are increasingly viewed as world simulators for embodied agents, yet their pretraining on internet-scale generic vid

Retrieved Images as Visual Thought: Training-Free Multimodal In-Context Learning for the Open-vs-Closed Gap

arXiv:2607.00606v1 Announce Type: new Abstract: Recent work on Thinking with Images makes vision a dynamic part of reasoning, but does so through generation: the model invokes external tools, synthesi

Right in the Right Way: LM Training with Verifiable Rewards and Human Demonstrations

arXiv:2607.01181v1 Announce Type: cross Abstract: RL with verifiable rewards (RLVR) has emerged as a powerful paradigm for training LMs on tasks with well-defined success metrics, such as code generat

RoadBench: Benchmarking MLLMs on Fine-Grained Spatial Understanding and Reasoning under Urban Road Scenarios

arXiv:2511.18011v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have demonstrated powerful capabilities in general spatial understanding and reasoning. However, their fine

Robust 3D Alignment of Generative Reconstructions via Partial Monocular Observations

arXiv:2607.00498v1 Announce Type: new Abstract: Aligning generative 3D reconstructions with partial monocular observations is a critical but under-explored challenge in computer vision. This task is i

SAOT: Self-Supervised Continual Graph Learning with Structure-Aware Optimal Transport

arXiv:2607.00377v1 Announce Type: new Abstract: Self-supervised Continual Graph Learning (CGL) aims to successively learn from a graph sequence with different tasks without label supervision - a parad

Seahorse: A Unified Benchmarking Framework for Spatiotemporal Event Modeling

arXiv:2607.01022v1 Announce Type: new Abstract: Spatiotemporal point processes (STPPs) model event data in continuous time and space, with applications in mobility, epidemiology, and public safety. Re