Search: “context”

arXiv:2604.21229v1 Announce Type: cross Abstract: Large language model assistants are increasingly expected to retain and reason over information accumulated across many sessions. We introduce Engrama

arXiv:2510.18914v4 Announce Type: replace-cross Abstract: Large language models often display undesirable behaviors embedded in their internal representations, undermining fairness, inconsistency drif

arXiv:2509.21976v3 Announce Type: replace-cross Abstract: Referring expression understanding in remote sensing poses unique challenges, as it requires reasoning over complex object-context relationshi

arXiv:2604.21871v1 Announce Type: new Abstract: Human moral judgment is context-dependent and modulated by interpersonal relationships. As large language models (LLMs) increasingly function as decisio

arXiv:2604.21767v1 Announce Type: new Abstract: Online misinformation is one of the most challenging issues lately, yielding severe consequences, including political polarization, attacks on democracy

🐳Ollama is working to have DeepSeek-V4-Pro and Flash available on Ollama's cloud. 🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length. 🔹 Dee

Organizations racing to deploy agentic AI are discovering that raw model performance is only part of the equation — context engineering is the key to managing decades of unstructured, ungoverned data

I cannot provide an accurate summary for this entry as the text appears incomplete and lacks sufficient context. The post fragment references o3 (likely an AI model), GPT-5.5, and discusses timeline/e

The search didn't return the specific Reddit post. Based on the context that this is from r/StableDiffusion (an active community for the open-source text-to-image AI model), the post likely discusses

arXiv:2604.21860v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into sensitive workflows, raising the stakes for adversarial robustness and safety. This pape

arXiv:2412.03594v3 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly play an important role in a wide range of information processing and management tasks in industry. M

arXiv:2604.20370v1 Announce Type: new Abstract: Forecasting the life-cycle trajectory of a newly launched product is important for launch planning, resource allocation, and early risk assessment. This

arXiv:2604.19816v1 Announce Type: new Abstract: The Transformer, a breakthrough architecture in artificial intelligence, owes its success to the attention mechanism, which utilizes long-range interact

arXiv:2602.09781v2 Announce Type: replace-cross Abstract: This study investigates the explainability of generative diffusion models in the context of medical imaging, focusing on Magnetic resonance im

arXiv:2503.08321v2 Announce Type: replace Abstract: Vision graph neural networks have emerged as a popular approach for modeling the global and spatial context for image recognition. However, a signif

arXiv:2603.27518v2 Announce Type: replace Abstract: Aligned language models that are trained to refuse harmful requests also exhibit over-refusal: they decline safe instructions that seemingly resembl

arXiv:2604.20474v1 Announce Type: new Abstract: The points on the point clouds that can entirely outline the shape of the model are of critical importance, as they serve as the foundation for numerous

arXiv:2604.20598v1 Announce Type: cross Abstract: Modern retrieval-augmented generation (RAG) systems treat vector embeddings as static, context-free artifacts: an embedding has no notion of when it w

arXiv:2604.19934v1 Announce Type: new Abstract: We study how large language models recall relational knowledge during text generation, with a focus on identifying latent representations suitable for r

arXiv:2511.19328v2 Announce Type: replace Abstract: Language modeling has shown us that transformers can discover latent structure from context, but the dynamics of how they acquire different componen

This post appears to reference regulatory or policy 'clampdowns' on AI, with the author expressing anticipation that OpenAI will face similar restrictions. Without access to the full context or surrou

Company-wise memory in Amazon Bedrock, powered by Amazon Neptune and Mem0, provides AI agents with persistent, company-specific context—enabling them to learn, adapt, and respond intelligently across

The era of agentic AI is accelerating from human- to machine-speed operations, while also creating profound stress on legacy technology infrastructure. This new reality pushes foundational systems to

arXiv:2604.18603v1 Announce Type: cross Abstract: Bidirectional transformers are the foundation of many sequence modeling tasks across natural, biological, and chemical language domains, but they are

We are officially moving past the era of one-size-fits-all AI. Enterprises today require highly specialized, role-specific tools to drive real productivity — but they cannot afford to sacrifice securi

arXiv:2604.18652v1 Announce Type: cross Abstract: The transition of agentic AI from brittle prototypes to production systems is stalled by a pervasive crisis of craft. We suggest that the prevailing o

arXiv:2604.19522v1 Announce Type: new Abstract: Bimanual mobile manipulation requires a seamless integration between high-level semantic reasoning and safe, compliant physical interaction - a challeng

arXiv:2604.18791v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models fail systematically on long-horizon manipulation tasks despite strong short-horizon performance. We show that this

arXiv:2604.19193v1 Announce Type: new Abstract: Despite remarkable progress toward general-purpose video models, a critical question remains unanswered: how far are these models from achieving true mu

OpenAI introduced workspace agents in ChatGPT, a new feature that enables shared agents capable of managing complex tasks and extended workflows across multiple tools and team members. These agents ar

arXiv:2604.18897v1 Announce Type: new Abstract: We present a systematic empirical study of prompt engineering for formal mathematical reasoning in the context of the SAIR Equational Theories Stage 1 c

arXiv:2604.18940v1 Announce Type: new Abstract: Autonomous driving systems often degrade under adverse visibility conditions-such as rain, nighttime, or snow-where online scene geometry (e.g., lane di

arXiv:2601.14152v2 Announce Type: replace-cross Abstract: Large language models exhibit surprising sensitivity to the structure of the prompt, but the mechanisms underlying this sensitivity remain poo

arXiv:2506.18871v4 Announce Type: replace-cross Abstract: In this work, we introduce OmniGen2, a versatile and open-source generative model designed to provide a unified solution for diverse generatio

Pay attention to this one, AI devs. This is particularly interesting if you work with long-horizon terminal agents that often drown in their own observations. TACO is a self-evolving framework that au

arXiv:2510.10866v3 Announce Type: replace-cross Abstract: Measuring dataset similarity is fundamental in machine learning, particularly for transfer learning and domain adaptation. In the context of s

arXiv:2602.02063v2 Announce Type: replace-cross Abstract: Automated vehicles lack natural communication channels with other road users, making external Human-Machine Interfaces (eHMIs) essential for c

This article likely explores the integration of Model Context Protocol (MCP) with Pinecone's skills, CLI tools, and plugin ecosystem for building AI applications. It probably covers how developers can

arXiv:2506.01687v3 Announce Type: replace Abstract: Subword-level understanding is integral to numerous tasks, including understanding multi-digit numbers, spelling mistakes, abbreviations, rhyming, a

arXiv:2604.16324v1 Announce Type: new Abstract: The activation memory required for exact backpropagation scales linearly with network depth, context length, and feature dimensionality, forming an O(L

arXiv:2604.17085v1 Announce Type: new Abstract: The interpretation of implicit meanings is an integral aspect of human communication. However, this framework may not transfer to interactions with Larg

arXiv:2604.16826v1 Announce Type: new Abstract: Merging separately trained LoRA adapters is a practical alternative to joint multi-task training, but it often hurts performance. Existing methods usual

fun off-the-cuff harness + agent engineering sesh with @dexhorthy @vaibcode @GeoffreyHuntley - a lot of good harness/agent design we’re doing today is still good context engineering, remember tool cal

arXiv:2604.17721v1 Announce Type: new Abstract: We address the challenge of point cloud registration using color information, where traditional methods relying solely on geometric features often strug

arXiv:2604.18260v1 Announce Type: new Abstract: Multimodal large language models have demonstrated remarkable capabilities in 2D vision, motivating their extension to 3D scene understanding. Recent st

arXiv:2604.18223v1 Announce Type: new Abstract: Vision-and-Language Navigation requires agents to follow natural-language instructions in visually changing environments. A central challenge is the dyn