Search: “retrieval”

arXiv:2604.05549v2 Announce Type: replace Abstract: With the widespread application of LLM-based agents across various domains, their complexity has introduced new security threats. Existing red-team

arXiv:2603.28287v2 Announce Type: replace Abstract: Despite the growing need for data of more and more sophisticated 3D reconstruction pipelines, we can still observe a scarcity of suitable public dat

this is a fundamental building block for `deepagents deploy` we're designing a memory layer built for multi-tenant systems, so memory can be scoped to a user, agent, or organization please dm me if th

arXiv:2604.11661v1 Announce Type: cross Abstract: Large language models (LLMs) have recently gained significant attention as a promising approach to accelerate scientific discovery. However, their app

arXiv:2604.10110v1 Announce Type: new Abstract: Large Language Models (LLMs) have become a key foundation for enabling personalized smart home experiences. While existing studies have explored how sma

arXiv:2604.11036v1 Announce Type: cross Abstract: Scientific fact-checking is vital for assessing claims in specialized domains such as biomedicine and materials science, yet existing systems often ha

arXiv:2604.11668v1 Announce Type: new Abstract: The growing availability of co-located geospatial data spanning aerial imagery, street-level views, elevation models, text, and geographic coordinates o

arXiv:2601.06165v2 Announce Type: replace-cross Abstract: Current vision-language benchmarks predominantly feature well-structured questions with clear, explicit prompts. However, real user queries ar

arXiv:2604.10787v1 Announce Type: new Abstract: Idiomatic reasoning, deeply intertwined with metaphor and culture, remains a blind spot for contemporary language models, whose progress skews toward su

arXiv:2512.17012v3 Announce Type: replace Abstract: Despite advances in Multimodal LLMs (MLLMs), their ability to reason over 3D structures and temporal dynamics remains limited, constrained by weak 4

arXiv:2604.08610v1 Announce Type: new Abstract: This paper presents a semi-automated framework for transforming two-dimensional miniatures from medieval manuscripts into three-dimensional digital mode

arXiv:2604.03512v2 Announce Type: replace Abstract: Outage management in large-scale cloud operations remains heavily manual, requiring rapid triage, cross-team coordination, and experience-driven dec

arXiv:2604.08552v1 Announce Type: cross Abstract: Scientific metadata are often incomplete and noncompliant with community standards, limiting dataset findability, interoperability, and reuse. When re

Build **b8779** is an incremental release of [llama.cpp](https://github.com/ggml-org/llama.cpp), an open-source C/C++ framework for running large language model inference locally and in the cloud. Lik

arXiv:2604.09414v1 Announce Type: cross Abstract: Learning-to-Defer routes each input to the expert that minimizes expected cost, but it assumes that the information available to every expert is fixed

DigitalOcean's Gradient AI Platform enables developers to build intelligent documentation agents that can automatically generate, maintain, and query technical documentation using large language model

This r/ChatGPT Reddit thread discusses user observations of ChatGPT inventing non-existent words, a behavior rooted in how large language models generate text — by predicting and assembling tokens (su

arXiv:2604.08846v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have been shown to be vulnerable to malicious queries that can elicit unsafe responses. Recent work uses prom

arXiv:2512.19396v3 Announce Type: replace Abstract: Contemporary GUI agents, while increasingly capable due to advances in Large Vision-Language Models (VLMs), often operate with a critical limitation

arXiv:2604.08556v1 Announce Type: cross Abstract: What exactly do efficient sequence models gain over simple temporal averaging? We use exponential moving average (EMA) traces, the simplest recurrent

arXiv:2604.09249v1 Announce Type: new Abstract: Fashion understanding requires both visual perception and expert-level reasoning about style, occasion, compatibility, and outfit rationale. However, ex

arXiv:2604.08896v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) have accelerated progress in domain-oriented AI, yet their development in geoscience and rem

This r/MachineLearning discussion thread centers on a hands-on workshop covering context engineering — the process of designing and optimizing the information an AI agent sends to and receives from a

arXiv:2604.09075v1 Announce Type: new Abstract: Large language models increasingly operate under multiple instructions from heterogeneous sources with different authority levels, including system poli

This r/ollama community thread discusses methods that users employ to inject personal context — such as notes, documents, and preferences — into locally-run AI models via Ollama. Common approaches exp

arXiv:2604.08966v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have advanced Video Temporal Grounding (VTG), existing methods often couple output paradigms with differe

arXiv:2604.08762v1 Announce Type: cross Abstract: Understanding instructional videos requires recognizing fine-grained actions and modeling their temporal relations, which remains challenging for curr

arXiv:2604.08970v1 Announce Type: cross Abstract: We study predictive multilingual evaluation: estimating how well a model will perform on a task in a target language when direct benchmark results are

arXiv:2604.09167v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance in multimodal understanding and reasoning, yet grounded reasoning in 3D scenes remains un

arXiv:2604.08995v1 Announce Type: new Abstract: With the advancement of interactive video generation, diffusion models have increasingly demonstrated their potential as world models. However, existing

arXiv:2604.07956v2 Announce Type: replace Abstract: Industry classification schemes are integral parts of public and corporate databases as they classify businesses based on economic activity. Due to

arXiv:2604.09021v1 Announce Type: cross Abstract: Auditory large language models (ALLMs) have demonstrated strong general capabilities in audio understanding and reasoning tasks. However, their reliab

arXiv:2604.08579v1 Announce Type: cross Abstract: We study cross-modal alignment between independently pretrained vision (DINOv2) and language (all-MiniLM-L6-v2) encoders using the functional map fram

arXiv:2506.17310v3 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) demonstrate strong performance across domains, their long-context capabilities are limited by transient neu

arXiv:2512.02231v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) are expected to jointly interpret vision, audio, and language, yet existing video benchmarks rarely a

arXiv:2604.09037v1 Announce Type: cross Abstract: Current video benchmarks for multimodal large language models (MLLMs) focus on event recognition, temporal ordering, and long-context recall, but over

arXiv:2604.08597v1 Announce Type: cross Abstract: Extracting structured knowledge from unstructured data still faces practical limitations: entity and event extraction pipelines remain brittle, knowle

arXiv:2602.17330v3 Announce Type: replace-cross Abstract: Comparative analysis of adaptive immune repertoires at population scale is hampered by two practical bottlenecks: the near-quadratic cost of p

arXiv:2604.09067v1 Announce Type: new Abstract: Data augmentation is a crucial technique for improving model generalization and robustness, particularly in deep learning models where training data is

Harrison Chase discusses the tradeoff between speed and focus when building a core product using a frontier model versus developing more customized solutions. Using a frontier model with a standard ha

arXiv:2604.09150v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance on complex tasks by leveraging long Chain-of-Thought (CoT), but often suffer from overthinking,

arXiv:2604.09197v1 Announce Type: cross Abstract: Purpose. High-grade serous ovarian carcinoma (HGSOC) is characterized by pronounced biological and spatial heterogeneity and is frequently diagnosed a

This Reddit post from r/MachineLearning announces a build-from-scratch Python book focused on the engineering infrastructure surrounding AI systems — the components beyond the model call itself, such

arXiv:2602.17667v2 Announce Type: replace-cross Abstract: In video search systems, user historical behaviors provide rich context for identifying search intent and resolving ambiguity. However, tradit

This Reddit discussion explores the practical trade-offs of storing ArcFace face recognition embeddings in pgvector's `HALFVEC` type, which uses 16-bit floating point numbers to represent vector compo

Build b8766 is a numbered incremental release of llama.cpp, the open-source C/C++ framework for running large language model inference locally. Like other builds in its rapid release cycle, it likely