Search: “models”

b9056 is a release of llama.cpp, a C/C++ implementation for LLM inference . The project enables users to run LLaMA models on consumer hardware without expensive GPUs or cloud infrastructure . This rel

Release b9063 is a build of llama.cpp, a project for LLM inference in C/C++. llama.cpp enables efficient large language model execution on consumer hardware through optimized implementations and quant

arXiv:2602.03452v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) is effective for training large language models on deterministic outcome reasoning tasks. Prio

arXiv:2605.04711v1 Announce Type: cross Abstract: Optimizer states occupy massive GPU memory in large-scale model training. However, gradients in different network blocks exhibit distinct behaviors, s

arXiv:2605.03278v2 Announce Type: cross Abstract: Doubly Robust (DR) estimation of treatment effect relies on an untestable assumption that is the absence of unobserved confounding. This assumption is

arXiv:2605.04477v1 Announce Type: new Abstract: Online reinforcement learning from human feedback (RLHF) has emerged as a promising paradigm for aligning large language models (LLMs) by continuously c

arXiv:2605.04418v1 Announce Type: new Abstract: The empirical success of large language model (LLM) pre-training relies heavily on heuristic stabilization techniques, such as explicit normalization la

arXiv:2605.04068v1 Announce Type: new Abstract: The use of artificial intelligence in supply chain forecasting has attracted many scientific studies for several decades. However, the process of select

arXiv:2601.03166v2 Announce Type: replace Abstract: Choosing a suitable ML model is a complex task that can depend on several objectives, e.g., accuracy, fairness, or energy consumption. In practice,

arXiv:2605.04164v1 Announce Type: new Abstract: Wildfires are a major producer of fine particulate matter, impacting human health and the electrical grid. Accurately forecasting smoke impacts over lon

Enterprise AI deployment has fundamentally expanded the cybersecurity attack surface, turning data pipelines, model training environments, identity management systems and supply chains into prime targ

arXiv:2605.04085v1 Announce Type: cross Abstract: Objectives: Large language models (LLMs) are increasingly used for clinical text summarization, yet structured methods to assess associated patient sa

arXiv:2605.04501v1 Announce Type: new Abstract: In recent years, object detection has achieved significant progress, especially in the field of open-vocabulary object detection. Unlike traditional met

arXiv:2605.04993v1 Announce Type: new Abstract: Accurate forecasting of electric vehicle (EV) charging demand is critical for grid stability, infrastructure planning, and real-time charging optimizati

arXiv:2602.23547v2 Announce Type: replace Abstract: Sentences like 'She will go to France or Spain, or perhaps to Germany or France.' appear formally redundant, yet become acceptable in contexts such

arXiv:2604.07401v2 Announce Type: replace-cross Abstract: We study the thermodynamic memory capacity of modern Hopfield networks (Dense Associative Memory models) with continuous states under geometri

This post from Pinecone references a full demonstration video from Google DeepMind, likely showcasing a new AI model, research breakthrough, or technical capability developed by DeepMind. The video li

arXiv:2605.04643v1 Announce Type: new Abstract: Approximating the ideological position of Members of Parliament (MPs) is a fundamental task in political science, helping researchers understand legisla

arXiv:2605.04581v1 Announce Type: new Abstract: Light field (LF) image super-resolution benefits from Epipolar Plane Images (EPIs), whose line slopes explicitly encode disparity. However, existing Tra

arXiv:2605.04500v1 Announce Type: new Abstract: Low-resource language varieties used by specific groups remain neglected in the development of Multilingual Language Models. A great deal of cross-lingu

arXiv:2602.07608v2 Announce Type: replace Abstract: Metastatic Progression remains the leading cause of cancer-related mortality, yet predicting whether a primary tumor will metastasize and where it w

arXiv:2605.04752v1 Announce Type: new Abstract: Accurate traffic congestion classification requires models that jointly capture roadway scene context and non-stationary traffic motion, yet most prior

arXiv:2512.17795v2 Announce Type: replace-cross Abstract: The unprecedented proliferation of digital data presents significant challenges in access, integration, and value creation across all data-int

It's a bit rare for me to agree with @hlntnr, @_NathanCalvin, AND @AdamThierer on something. But we all agree that government FDA-style pre-approval for AI models is a bad idea. Check out this great a

Learn how to structure your AI stack. Our co-founder @the_bunny_chen talks with @theinfrapod's @tnachen and @ianlivingstone about inference optimization, the open vs. closed model debate, and building

arXiv:2605.03159v1 Announce Type: new Abstract: As autonomous agents become increasingly sophisticated, validating their sequential behavior presents a significant challenge. Traditional testing appro

arXiv:2505.00753v5 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have sparked growing interest in building fully autonomous agents. However, fully autonomous LLM-bas

arXiv:2605.04295v1 Announce Type: new Abstract: LLMs' overconfidence, particularly when hallucinating, poses a significant challenge for the deployment of the models in safety-critical settings and ma

arXiv:2605.05115v1 Announce Type: new Abstract: Neural representations carry rich geometric structure; but does that structure causally shape behavior? To address this question, we intervene along pat

arXiv:2605.04180v1 Announce Type: new Abstract: Large Language Models exhibit strong reasoning and semantic understanding capabilities but often hallucinate in domains that require expert knowledge, a

arXiv:2605.04772v1 Announce Type: new Abstract: Access to diverse, well-annotated medical images with interactive learning tools is fundamental for training practitioners in medicine and related field

arXiv:2602.02282v2 Announce Type: replace Abstract: Inferring spatial transcriptomics (ST) from histology enables scalable histogenomic profiling, yet current methods are largely restricted to single-

A LoRA adapter for FLUX.2 Klein that enables camera angle control across 72 unique positions using 8 azimuths, 9 elevations, and 3 distances . The model rotates objects through 360° azimuth and 60° el

arXiv:2511.09537v2 Announce Type: replace Abstract: We introduce negative space learning machine translation (NSL-MT), a training method for underresourced languages, that augments limited parallel da

one of the features i'm most excited about in our upcoming langgraph release is delta channels! the langgraph runtime lets you 'checkpoint' agent progress at every step (model call, tool call, hooks).

arXiv:2605.04364v1 Announce Type: new Abstract: We study online prediction for marginally stable, partially observed linear dynamical systems under nonstochastic disturbances. Our objective is to mini

arXiv:2605.04955v1 Announce Type: new Abstract: When a machine learning (ML) model forecasts an undesired event, one often seeks a decision to avoid it, known as the avoiding undesired future (AUF) pr

arXiv:2605.05084v1 Announce Type: new Abstract: Domain shift remains a key challenge in deploying machine learning models to the real world. Unsupervised domain adaptation (UDA) aims to address this b

arXiv:2605.03143v1 Announce Type: cross Abstract: Recent advances in large language models have led to the rise of software systems (i.e. agents) that execute with increasing autonomy on behalf of use

arXiv:2605.05120v1 Announce Type: new Abstract: An interpretable and scalable framework for decoding driving behaviors from multimodal physiological signals is proposed in this study. We utilize multi

arXiv:2510.25224v3 Announce Type: replace Abstract: While Large Language Models (LLMs) are increasingly used in agentic frameworks to assist individual users, there is a growing need for agents that c

arXiv:2505.18466v2 Announce Type: replace Abstract: Evaluations of Large Language Models (LLMs) often overlook intersectional and culturally specific biases, particularly in underrepresented multiling

arXiv:2605.04523v1 Announce Type: new Abstract: We present our winning system for Task~B (generation with reference passages) in SemEval-2026 Task~8: MTRAGEval. Our method is a heterogeneous ensemble

arXiv:2605.04920v1 Announce Type: cross Abstract: Compositional generalization refers to correctly interpret novel combinations of known primitives, which remains a major challenge. Existing approache

Research from Prof Julian Togelius found that despite AI's well-documented victories in chess, Go, and Atari games, humans still learn unfamiliar video games far faster than any AI model. #NYUTandonMa

arXiv:2605.04913v1 Announce Type: new Abstract: LLM post-training typically propagates task gradients through the full depth of the model. Although this end-to-end structure is simple and general, it