Knowledge catalogue
arXiv:2608.04586v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have achieved significant success in speech-to-text translation (S2TT). However, when processing multilingual
arXiv:2608.05042v1 Announce Type: new Abstract: Leveraging pre-trained vision-language models (VLMs) to construct vision-language-action (VLA) models has emerged as a promising paradigm for 3D robot m
Broadcom Inc. today introduced new security, performance and automation capabilities for VMware Cloud Foundation that are intended to help enterprises defend private clouds against artificial intellig
As engineering teams adopt coding agents like Codex, leaders need visibility into adoption, consumption, and reliability. This post shows how to route Codex OpenTelemetry metrics through a local colle
PDI Technologies built PDI Brew, an agentic platform on AWS where non-technical employees describe a tool in plain English and receive a fully provisioned, multi-tenant web application in seconds. See
arXiv:2608.04013v1 Announce Type: cross Abstract: Recent advances in Multimodal Emotion Recognition in Conversations (MERC) highlight its reliance on complete multimodal inputs. However, real-world da
arXiv:2608.04746v1 Announce Type: new Abstract: LLM agents that persist across sessions accumulate stored memories whose validity varies enormously by content type, yet existing memory architectures t
arXiv:2608.04663v1 Announce Type: new Abstract: Cooperative multi-agent reinforcement learning often adds social terms to individual rewards, yet the scale of those terms is usually chosen by hand. We
arXiv:2512.20661v2 Announce Type: replace Abstract: Transformer-based pre-trained language models (PLMs) excel in text classification but suffer from attention dilution and attention sink effects, for
arXiv:2608.04051v1 Announce Type: new Abstract: Real-world time series are often governed by recurring patterns, but their dominant periods may vary across datasets, forecasting settings, and individu
arXiv:2602.06337v2 Announce Type: replace-cross Abstract: Causal inference is essential for decision-making but remains challenging for non-experts. While large language models (LLMs) show promise in
arXiv:2608.05025v1 Announce Type: new Abstract: Joint Energy-Based Models (JEM) unify classification and generation within a single network and support out-of-distribution (OOD) detection. Canonical J
arXiv:2608.05085v1 Announce Type: cross Abstract: Systems that automate scientific discovery must repeatedly decide which experiment to run, which hypothesis to test, which tool to build, and when to
arXiv:2608.04509v1 Announce Type: new Abstract: Vision-language systems combine images with retrieved text, but these sources can disagree or jointly fail to support an answer. Reliable models must id
arXiv:2608.04515v1 Announce Type: cross Abstract: Slice-based MLLMs leverage mature 2D encoders by representing 3D volumes as sequences of 2D slices. However, this slice-wise formulation produces thou
arXiv:2608.04576v1 Announce Type: new Abstract: Humanitarian reports are long, noisy, and multi-topic, making it difficult to consolidate decision-relevant causal evidence. We present a ReliefWeb stud
arXiv:2608.04735v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring is increasingly treated as an important safety layer for frontier reasoning models. Most monitorability evaluations st
arXiv:2511.19418v3 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) excel at reasoning in linguistic space but struggle with perceptual understanding that requires dense visual per
arXiv:2608.05124v1 Announce Type: cross Abstract: Long context reasoning in large language models (LLMs) is usually constrained by the fact that a single inference trajectory has to simultaneously exp
Up until now, I’d always assumed it was basically just transcribing what I said, feeding the text into the model, and reading the response back. So out of curiosity, I asked if it could actually tell
arXiv:2608.04035v1 Announce Type: cross Abstract: The wide adoption of Vision Transformers (ViTs) in safety-critical applications raises reliability concerns related to hardware faults. Algorithm-Base
arXiv:2608.04942v1 Announce Type: cross Abstract: CheMLFlow is an open-source platform for building and executing end-to-end, high-throughput, and agentic workflows for scientific and technological ap
arXiv:2605.12153v2 Announce Type: replace-cross Abstract: We present the Curated Industrial Developer Repository (CIDR), a large-scale dataset of real-world software repositories collected from indust
arXiv:2608.04302v1 Announce Type: new Abstract: Benchmarking video-language models has largely focused on short clips and single-sentence metrics, leaving open whether current systems can generate acc
arXiv:2512.22969v2 Announce Type: replace Abstract: Conventional object detectors rely on cross-entropy classification, which can be vulnerable to class imbalance and label noise. We propose CLIP-Join
C’mon, it’s not game over for Google Seven reasons why not, excerpted from my newsletter: Jeff Dean and Demis Hassabis are the two most important AI executives at Google. Jeff is leaving and Demis is
arXiv:2608.05149v1 Announce Type: new Abstract: Current instruction-based image retrieval systems are powerful but limited to single-turn interactions, failing to capture the iterative nature of compl
arXiv:2608.04396v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have driven significant progress in robotic manipulation, yet they fundamentally struggle with the vision-override p
arXiv:2608.04559v1 Announce Type: new Abstract: Although deep neural network-based remote sensing object detectors have achieved strong performance, they remain vulnerable to adversarial perturbations
arXiv:2608.04366v1 Announce Type: cross Abstract: While retrieval-augmented generation systems partially address the hallucination issues in large language models, it also introduces new vulnerabiliti
arXiv:2508.13661v4 Announce Type: replace Abstract: Centralized Training with Decentralized Execution (CTDE) is the dominant paradigm in multi-agent reinforcement learning (MARL), enabling agents to a
arXiv:2608.04336v1 Announce Type: cross Abstract: Code generation systems make each LLM call with a model, a prompt, and decoding settings. However, existing optimization methods usually tune only par
arXiv:2608.04274v1 Announce Type: cross Abstract: Social media recommendation feeds often optimize for users' immediate impulses rather than preferences they would hold after deeper reflection. Some s
Learn how to configure rate limits on Amazon Bedrock AgentCore gateway to enforce per-user and per-target traffic controls. Define request, token, and connection limits scoped by JWT claims or IAM ide
Anthropic PBC today disclosed that it plans to develop a custom artificial intelligence chip. A spokesperson told Business Insider that the company will co-design the processor with its future large l
Congrats to @mattrubens and the Roomote team on the launch. Builders can use Together AI as an inference provider in Roomote and assign different open models to coding, planning, vision, and review ac
arXiv:2608.04926v1 Announce Type: cross Abstract: As chart images, tabular data, and visualization code play increasingly important roles across diverse domains, cross-representation understanding acr
arXiv:2608.04956v1 Announce Type: new Abstract: Recent video models increasingly support generation, reference conditioning, and editing within a single model, yet typically expose them as separate op
arXiv:2608.04830v1 Announce Type: new Abstract: Memory is essential as language agents move from isolated tasks to long-horizon, stateful workflows, yet existing evaluations often reduce it to retriev
arXiv:2608.04778v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) incorporate governing equations into neural-network training and can approximate PDE solutions without requirin
arXiv:2510.14190v3 Announce Type: replace Abstract: Diffusion models excel at generation, but their latent spaces are high dimensional and not explicitly organized for interpretation or control. We in
Learn about new capabilities in Amazon Bedrock AgentCore: temporal policies powered by Dogwood, a new open source policy language for AI agents, and rate limiting on the gateway. These features give y
arXiv:2511.09002v3 Announce Type: replace-cross Abstract: Self-consuming generative models have received significant attention over the last few years. In this paper, we study a self-consuming generat
arXiv:2608.04865v1 Announce Type: new Abstract: Event cameras, also known as neuromorphic cameras, have gained significant attention in recent years due to their high temporal resolution, high dynamic
arXiv:2608.05107v1 Announce Type: new Abstract: AI-supported care planning can help clinicians, patients, caregivers, and care teams coordinate complex decisions across clinical, functional, psychosoc
arXiv:2510.15395v2 Announce Type: replace Abstract: An AI agent will learn a desired goal more effectively if it does not resist the training process, but many partially learned goals incentivize an A
arXiv:2608.04604v1 Announce Type: new Abstract: Source-free domain adaptation (SFDA) adapts a source-trained model to an unlabeled target domain without source data, a practical setting under privacy
arXiv:2608.04333v1 Announce Type: new Abstract: Large language model (LLM) configuration evaluation is challenging due to limited evaluation budgets, varying costs, and multiple competing objectives.
arXiv:2608.04525v1 Announce Type: new Abstract: Scene text image super-resolution (STISR) aims to recover visually plausible appearance while preserving character semantics from degraded inputs. Exist
critical history and context that a lot of people have conveniently forgotten For a very long time most high-performing AI models were end-to-end neural models; vector input -> vector output, with onl
arXiv:2608.04655v1 Announce Type: cross Abstract: Curvilinear structure analysis is an important and fundamental task in multimedia. However, the controllable generation of images with precise curvili
arXiv:2503.14833v2 Announce Type: replace-cross Abstract: One of the bottlenecks in robotic intelligence is the instability of neural network models. This leads to risks when applying intelligence in
Cursor now supports Agent Plugins, an open standard for bundling skills and MCP servers for use across agents. https://x.com/vercel/status/2085398393179005223?s=20 Introducing Agent Plugins, an open s
arXiv:2608.04444v1 Announce Type: cross Abstract: Large language models (LLMs) often generate inaccurate answers due to their reliance on static internal knowledge. Retrieval-augmented generation (RAG
arXiv:2608.04622v1 Announce Type: new Abstract: AI agents have emerged as a powerful new paradigm in generative image synthesis, enabling systems to perform complex semantic reasoning rather than pass
arXiv:2608.05120v1 Announce Type: new Abstract: Kinetic model discovery is a central challenge in chemical engineering, as accurate rate expressions are essential for understanding and controlling che
arXiv:2602.07453v2 Announce Type: replace Abstract: Decision tree ensembles are widely used in critical domains, making robustness and sensitivity analysis essential to their trustworthiness. We study
arXiv:2608.04322v1 Announce Type: new Abstract: Task-specific fine-tuning can improve the performance of large language models (LLMs) on downstream tasks. However, our study reveals that task-specific
arXiv:2607.14407v3 Announce Type: replace-cross Abstract: Many signal processing systems ultimately exist to {act}. Whenever the state variable that determines the action to be taken by a decision mak
Large language models (LLMs) with integrated search tools show strong promise in open-domain question answering (QA), yet they often struggle to produce complete answer set to complex questions such a