Knowledge catalogue
arXiv:2606.11930v1 Announce Type: cross Abstract: Predicting psychological traits from asynchronous video interviews (AVIs) is a challenging multimodal learning problem because labeled datasets are li
arXiv:2606.12016v1 Announce Type: cross Abstract: Model post-training, and in particular reinforcement learning (RL), is one of the primary mechanisms by which developers can shape models' values and
arXiv:2509.10303v2 Announce Type: replace-cross Abstract: Online reinforcement learning (RL) approaches have demonstrated strong performance on Job Shop Scheduling (JSP) and Flexible JSP (FJSP) proble
arXiv:2606.11263v1 Announce Type: cross Abstract: Spectral methods rely fundamentally on the stability of principal eigenspaces under random perturbations. Classically, this stability is quantified by
arXiv:2509.25359v2 Announce Type: replace-cross Abstract: We present a systematic stress-test of geometric metrics for LLM evaluation. Rank-based geometric properties of internal representations have
arXiv:2601.00791v2 Announce Type: replace-cross Abstract: Verifying whether a language model is genuinely reasoning or pattern-matching remains an open problem: learned verifiers are expensive, and ou
arXiv:2606.11382v1 Announce Type: new Abstract: Deep learning models facilitate the discovery of molecules with tailored properties among billions of candidate compounds. However, the computational bu
arXiv:2606.11688v1 Announce Type: cross Abstract: Long-horizon LLM agents are not trusted to run unattended: with no human watching, they confidently report success they never verified. We treat hones
Google LLC today released DiffusionGemma, a large language model based on an emerging machine learning approach known as text diffusion. The company says the algorithm can generate text four times fas
arXiv:2509.16456v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in various domains, showing impressive potential on different tasks. Recently, reasoning LLMs hav
arXiv:2606.11817v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for code generation, raising concerns that they may be misused to produce malicious code. Meanwhile
arXiv:2606.11562v1 Announce Type: cross Abstract: Graph analysis underlies many applications whose answers cannot be looked up in a single record or retrieved along a path: laundering rings, drug repu
arXiv:2606.11898v1 Announce Type: new Abstract: Research on Text-Attributed Graphs (TAGs) has gained significant attention recently due to its broad applications across various real-world data scenari
arXiv:2511.07332v2 Announce Type: replace-cross Abstract: Building reliable computer-use agents requires grounding: accurately connecting natural language instructions to the correct on-screen element
arXiv:2606.11429v1 Announce Type: cross Abstract: Speech foundation models often struggle in low-resource domains due to domain mismatch and data scarcity. We propose Gumbel-BEARD, a domain adaptation
arXiv:2606.11963v1 Announce Type: new Abstract: Neural operators provide a powerful framework for learning solution mappings of partial differential equations directly in function space. However, many
arXiv:2606.12318v1 Announce Type: cross Abstract: Neural operators approximate mappings between function spaces, but often generalize poorly to other operators and usually require fine-tuning or retra
This post appears to be from Boris Cherny announcing or sharing content related to 'Code with Claude Tokyo,' likely a coding event, workshop, or community initiative involving Claude AI in Tokyo. The
Nous Research announced Hermes Agent, a system designed to provide greater autonomy and flexibility for AI agents in task execution and decision-making. The post likely highlights how this agent frame
arXiv:2606.11559v1 Announce Type: new Abstract: Reinforcement learning typically improves multi-turn agent capabilities through the terminal outcome of the trajectories, which makes it difficult to de
arXiv:2606.11744v1 Announce Type: cross Abstract: Large language models are now widely used for everyday learning, but the underlying interactions are typically unstructured chats rather than followin
arXiv:2411.12193v4 Announce Type: replace-cross Abstract: The rapid growth of distributed energy resources (DERs) presents both opportunities and operational challenges for electric grid management. A
arXiv:2601.03326v2 Announce Type: replace Abstract: PCA can be used for rotation invariant features, describing a shape with its p_{ab}=E[(x_i-E[x_a])(x_b-E[x_b])] covariance matrix approximating shap
arXiv:2606.11673v1 Announce Type: cross Abstract: Standard dot-product self-attention computes, in a single layer, only pairwise (order-2) interactions between tokens; representing a generic order-k i
arXiv:2606.11372v1 Announce Type: new Abstract: Piezoresistive tactile sensors are attractive for robotic manipulation because they are thin, lightweight, low-cost, and scalable to dense large-area se
arXiv:2606.12280v1 Announce Type: new Abstract: Post-training quantization lets large text-to-image diffusion transformers run on consumer GPUs, yet the hardware-specific trade-offs are seldom measure
Hot take on a bad day for OpenAI: WeWork’s IPO fell apart. I’ve been calling OpenAI the (possible) WeWork of AI for a long time. I will not be surprised if their IPO plans apart, too. Their apparent p
An astrophysicist leverages OpenAI's Codex AI model to accelerate the development of code for simulating black hole physics and behavior. Codex assists in generating complex scientific code more effic
arXiv:2509.11548v2 Announce Type: replace Abstract: Graphical user interface (GUI) grounding is a fundamental task for building GUI agents. However, general vision-language models (VLMs) struggle with
Organizations are increasingly focused on AI-native development architectures where frontier agents handle complex tasks including identity, state, policies, evals, and long-running workflows through
arXiv:2606.12182v1 Announce Type: new Abstract: Identifying the governing equations of complex dynamical systems remains a fundamental challenge across science and engineering. While early approaches
arXiv:2606.12407v1 Announce Type: new Abstract: General-purpose large language models (LLMs) are routinely used as baselines when evaluating specialized pathology models on whole-slide images (WSIs).
Gary Marcus discusses whether Section 230 of the Communications Decency Act adequately protects AI systems and companies from legal liability, suggesting that existing protections may not fully apply
arXiv:2606.11499v1 Announce Type: cross Abstract: The performance of modern language models depends critically on pretraining data composition. Yet existing data selection methods rely on auxiliary cl
arXiv:2606.12025v1 Announce Type: new Abstract: Finite element (FE) modeling of safety-critical infrastructure such as bridge barriers requires high-fidelity nonlinear dynamic analysis, yet the curren
arXiv:2602.19502v2 Announce Type: replace Abstract: Agentic AI systems are increasingly capable of autonomous data science workflows, yet clinical prediction tasks demand domain expertise that purely
arXiv:2606.11818v1 Announce Type: new Abstract: The handling of flexible materials is a difficult task to fully automate due to the challenges caused by the deformability of these types of objects. Me
A developer created a fully local, CPU-based voice interface for Ollama that enables hands-free conversation with AI models by combining three open-source components: Silero VAD (voice activity detect
I still feel this way, 8 years later. People sometimes ask if I think it's risky for everyone to have access to AI. I think it's MORE risky for an exclusive & homogeneous group alone to develop tech t
arXiv:2606.11875v1 Announce Type: new Abstract: Emotional validation - explicitly acknowledging that a user's feelings make sense - has proven therapeutic value but has received little computational a
arXiv:2606.11289v1 Announce Type: new Abstract: Diffusion models have consistently driven progress in text-to-image generation. However, it is challenging to attribute recent progress to specific mode
arXiv:2606.11652v1 Announce Type: new Abstract: This paper investigates reinforcement learning (RL) methods for improving tool-calling capabilities in multimodal small language model (SLM) agents. Whi
arXiv:2606.11722v1 Announce Type: cross Abstract: Finding interpretable directions in language-model representations is critical for understanding and controlling model behavior. Sparse autoencoders (
Ideogram 4 includes runtime safety filters powered by Hive for prompt and output moderation , with NSFW prompts blocked by displaying 'Image blocked by safety filter' . Users have reported false posit
Gary Marcus poses a philosophical question about emotional attachment to AI companies, likely exploring whether people have genuine emotional stakes in the success or failure of specific AI organizati
This post draws a sports analogy comparing the New York Knicks' comeback capability to OpenAI's competitive position against Anthropic in the AI industry. The tweet suggests optimism about OpenAI's ab
arXiv:2606.12378v1 Announce Type: cross Abstract: Physiological awareness is important for service, social, and assistive robots that interact with humans in everyday environments. Remote photoplethys
arXiv:2606.11884v1 Announce Type: new Abstract: This paper addresses the challenge of assessing image quality in ID cards in remote verification systems by applying capture-related quality measures fr
arXiv:2606.12200v1 Announce Type: cross Abstract: We study policy representation learning from unlabeled multi-policy behavioral data. Each episode is generated by a fixed policy, but policy labels ar
arXiv:2606.11643v1 Announce Type: new Abstract: Large language models often remain sensitive to answer format: a question solved correctly in one form may fail in another semantically equivalent form.
arXiv:2602.08986v2 Announce Type: replace-cross Abstract: In hierarchical multi-label classification, a persistent challenge is enabling model predictions to reach deeper levels of the hierarchy for m
arXiv:2307.01472v2 Announce Type: replace Abstract: We present a novel Diffusion Offline Multi-agent Model (DOM2) for offline Multi-Agent Reinforcement Learning (MARL). Different from existing algorit
arXiv:2606.11704v1 Announce Type: new Abstract: Human endurance in underwater locomotion is fundamentally restricted by high energetic demands to overcome drag and the finite supply of self-contained
arXiv:2606.11614v1 Announce Type: cross Abstract: Multimodal learning hinges on capturing redundant, unique, and synergistic information across modalities, which collectively constitute multimodal int
arXiv:2606.11440v1 Announce Type: new Abstract: Existing multi-agent LLM orchestration methods, ranging from brute-force ensembles to learned routers, select models and topologies based on task and mo
arXiv:2606.11629v1 Announce Type: cross Abstract: This manuscript proposes an integral formulation of the newly defined quadratic embedding method for identifying nonlinear systems (QENDy). In the ori
arXiv:2606.12086v1 Announce Type: new Abstract: Contextualized assessment offers high ecological validity for evaluating creativity but introduces a critical challenge: observed performance may be con
arXiv:2606.12207v1 Announce Type: cross Abstract: Embodied intelligence now spans navigation, household assistance, manipulation, autonomous driving, aerial agents, and multimodal large-model control.
arXiv:2606.11287v1 Announce Type: cross Abstract: Skin cancer is among the most prevalent malignancies worldwiAdbe satnradcitts early detection is essential for improving patient survival and reducing
arXiv:2601.14031v2 Announce Type: replace-cross Abstract: Forecasting intermittent time series, which contain zeros, is a crucial challenge in supply chains as inventory policies require probabilistic