Search: “models”

Ideogram 4.0 is a frontier text-to-image foundation model released as an open-weight model with a commercial license. The model delivers frontier-grade text rendering across languages, bounding-box la

arXiv:2606.05389v1 Announce Type: new Abstract: Lossy compression is essential for massive spatiotemporal data from scientific simulations. Learned compressors can achieve high compression ratios at m

arXiv:2606.05403v1 Announce Type: cross Abstract: Language models increasingly act as epistemic proxies, synthesizing evidence from multiple sources to inform decisions. Whether they evaluate the qual

arXiv:2601.21288v2 Announce Type: replace-cross Abstract: Autonomous driving is an important and safety-critical task, and recent advances in LLMs/VLMs have opened new possibilities for reasoning and

arXiv:2606.05354v1 Announce Type: new Abstract: Retinal blood vessel segmentation plays a vital role in the early detection of diabetic retinopathy and glaucoma. While recent deep learning models have

arXiv:2606.05535v1 Announce Type: new Abstract: Medical visual question answering (Med-VQA) has strong potential for clinical decision support by enabling AI models to interpret medical images and ans

Google's May 2026 AI updates center on the new 'agentic' era, featuring the Gemini 3.5 model and Gemini Omni for advanced reasoning and creation. Gemini Omni is a new model that can create anything fr

arXiv:2602.09464v2 Announce Type: replace-cross Abstract: Vericoding refers to the generation of formally verified code from rigorous specifications. Recent AI models show promise in vericoding, but a

arXiv:2510.11194v3 Announce Type: replace Abstract: Personalized alignment is crucial for enabling Large Language Models (LLMs) to engage effectively in user-centric interactions. However, current met

arXiv:2606.04072v1 Announce Type: cross Abstract: Deep learning models are increasingly central to autonomous vehicle (AV) pipelines, yet their integration has traditionally followed a monolithic desi

arXiv:2606.04915v1 Announce Type: new Abstract: Large language models reach 50 to 70% accuracy on causal reasoning benchmarks such as CLadder, but it is unclear whether this reflects structural reason

arXiv:2606.04115v1 Announce Type: cross Abstract: Quantizing large language models (LLMs) to low-precision floating-point representations is central to efficient deployment, yet applying a single bit-

arXiv:2606.04282v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are predominantly evaluated on free-form vision-language tasks such as visual question answering, captioning, a

arXiv:2606.04019v1 Announce Type: cross Abstract: Recent studies on sensor-language alignment have shown that two-stage frameworks can improve the semantic modeling ability of wearable-sensor human ac

Gemma4 is a language model available through Ollama's model library that users can download and run locally. The entry likely provides information about the model's specifications, capabilities, and h

arXiv:2606.04612v1 Announce Type: new Abstract: Large Language Models (LLMs) are vulnerable both to hallucination and adversarial manipulation. Although these problems are closely related, existing de

arXiv:2606.04339v1 Announce Type: new Abstract: Computational models of epilepsy promise patient-specific treatment design, but most optimization workflows still search for parameters that perform wel

Nemotron 3 Ultra, NVIDIA's advanced language model, is now accessible through Vercel's AI Gateway, enabling developers to integrate this model into their applications alongside other LLM options. The

arXiv:2511.05722v3 Announce Type: replace-cross Abstract: Large language models (LLMs) such as GPT-5 and Gemini 3 have pushed the frontier of automated reasoning and code generation. Yet current bench

arXiv:2606.04834v1 Announce Type: new Abstract: Minimum Description Length (MDL) formalizes the principle of Occam's razor by optimizing the total description length: L(model)+L(data | model). For seq

arXiv:2606.05070v1 Announce Type: new Abstract: Train delay prediction is an important problem for both passengers and railway operators, yet progress in the field remains difficult to assess due to t

arXiv:2603.10044v2 Announce Type: replace-cross Abstract: A safety score earned on a benchmark need not predict how the same model behaves once it is wrapped in an agentic scaffold the benchmark never

arXiv:2606.04454v1 Announce Type: new Abstract: Large language models have shown strong performance in natural language generation and downstream reasoning tasks, but they still struggle with logical

arXiv:2606.05165v1 Announce Type: cross Abstract: Training Data Attribution (TDA) seeks to trace a model's predictions back to its training data. The gold standard for TDA relies on causal interventio

arXiv:2606.04108v1 Announce Type: cross Abstract: Single-view 3D generative models have achieved impressive visual quality, yet they are not designed to satisfy structural or functional requirements,

arXiv:2606.03034v1 Announce Type: cross Abstract: Large language model (LLM) agents have begun to delegate work to one another. Protocols such as the Model Context Protocol (MCP) and the Agent2Agent p

arXiv:2606.02971v1 Announce Type: new Abstract: Extracting reporting obligations from EU legislation is critical for assessing and reducing regulatory reporting burden. However, distinguishing reporti

arXiv:2606.03331v1 Announce Type: cross Abstract: Consumer device repair is an important but underexplored testbed for large language models (LLMs). Repair tasks require reasoning over incomplete prob

arXiv:2606.02920v1 Announce Type: new Abstract: Language-model unlearning updates a trained model to behave as if it had not seen selected training examples, while preserving utility and avoiding cost

Gemma 4 12B is a newly released dense language model from Google available under the Apache 2.0 open license, designed for mid-sized computing resources that can run locally on personal computers. The

GPT-Rosalind is an OpenAI model with newly introduced capabilities designed to enhance its performance in specific tasks or domains. The update likely expands the model's functionality in areas such a

arXiv:2604.07123v2 Announce Type: replace Abstract: Large Language Models (LLMs) have been shown to contain biases in the process of integrating conflicting information when answering questions. Here

arXiv:2606.03303v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong informal mathematical reasoning but struggle to generate mechanically verifiable proofs in formal languages

arXiv:2606.03257v1 Announce Type: cross Abstract: Spiking Vision Transformer (SViT) models are promising low-power ViT models for solving vision-based tasks with state-of-the-art performance. However,

arXiv:2606.03935v1 Announce Type: cross Abstract: The ability to train spiking neural networks is essential for modeling biological neural networks as well as for neuromorphic computing. However, for

arXiv:2601.11429v2 Announce Type: replace-cross Abstract: Hallucination is a central failure mode of language models (LMs). We focus on hallucinations in response to questions like: 'Which instrument

arXiv:2606.02606v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed as continuously evolving services, where frequent base-model updates may invalidate previously

arXiv:2606.02664v1 Announce Type: cross Abstract: Latent state-space models are widely used to study partially observed dynamical systems, yet most formulations assume that process variability is inde

arXiv:2606.03606v1 Announce Type: cross Abstract: Large language models achieve strong performance on arithmetic reasoning benchmarks, and one common response to arithmetic brittleness is to delegate

Ollama v0.30.4 is a patch release addressing a bug in the llama-server component related to incorrect parameter wiring in the Gemma 4 model implementation. This fix ensures Gemma 4 models operate corr

arXiv:2606.03273v1 Announce Type: cross Abstract: Visual DeepSearch requires multimodal large reasoning model (MLRM) agents to answer complex visual queries by repeatedly inspecting image regions, gro

arXiv:2606.03837v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) and probing enable adaptation of foundation models using only a small number of trainable parameters, making it a

arXiv:2602.08873v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now used for academic expert recommendation. Existing audits typically evaluate such recommendations in isola

arXiv:2603.14465v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have evolved into tool-using agents, they remain brittle in long-horizon interactions. Unlike mathematical reason

NVIDIA announced three new offerings: Cosmos 3, an advanced video generation model; Nemotron 3 Ultra, an upgraded language model; and RTX Spark, likely a tool or framework for developers. These releas

arXiv:2606.00257v1 Announce Type: cross Abstract: Token-level credit assignment for language-model reinforcement learning is usually formulated as if the policy were fully trainable, while practical L