Knowledge catalogue
arXiv:2602.08167v2 Announce Type: replace-cross Abstract: Embodied Chain-of-Thought (CoT) reasoning has significantly enhanced Vision-Language-Action (VLA) models, yet current methods rely on rigid te
arXiv:2605.17537v1 Announce Type: new Abstract: 3D open-world environments with adversarial opponents remain a core challenge for reinforcement learning due to their vast state spaces. Effective reaso
arXiv:2605.17403v1 Announce Type: new Abstract: Rearranging the rows or columns of a sparse matrix using an appropriate ordering can significantly reduce fill-ins, i.e., new nonzeros introduced during
arXiv:2605.18557v1 Announce Type: new Abstract: The brain learns abstract representations of high-dimensional sensory input, but the plasticity rules that enable such learning are unknown. We study bi
arXiv:2605.17497v1 Announce Type: new Abstract: GRPO-style RLVR trains reasoning models from multiple on-policy attempts per prompt, but typically uses these attempts only through terminal rewards. We
arXiv:2605.17101v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is widely employed to mitigate risks such as hallucinations and knowledge obsolescence in medical question answer
arXiv:2605.18714v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) strive to consolidate visual understanding and visual generation within a single architecture. However, prevailing tr
arXiv:2605.18007v1 Announce Type: new Abstract: Rhetorical Role Labeling (RRL) assigns a functional role to each sentence in a document and is widely used in legal, medical, and scientific domains. Wh
arXiv:2605.16440v1 Announce Type: cross Abstract: Deep neural networks are vulnerable to adversarial perturbations, limiting deployment in safety-critical applications such as synthetic aperture radar
arXiv:2412.18158v2 Announce Type: replace Abstract: Learned image compression methods have shown impressive performance but are often highly specialized for either human perception or specific machine
arXiv:2605.18156v1 Announce Type: new Abstract: Lens flare removal is challenging due to the large spatial extent of flare artifacts and their entanglement with scene structures, while existing method
arXiv:2605.18101v1 Announce Type: cross Abstract: Urban Building Energy Modeling plays a critical role in achieving the United Nations' Sustainable Development Goals 7 and 11. Although existing studie
arXiv:2605.17724v1 Announce Type: cross Abstract: This paper compares gradient boosting and long short-term memory (LSTM) architectures for intraday directional prediction in Micro E-Mini Nasdaq 100 f
arXiv:2512.12598v3 Announce Type: replace Abstract: We focus on the foundational task of Scene Staging: given a reference scene image and a text condition specifying an actor category to be generated
arXiv:2601.18442v3 Announce Type: replace Abstract: Autonomous Vehicle (AV) requires rigorous testing in safety-critical scenarios for safety validation, yet its validation is hindered by the high cos
arXiv:2605.18039v1 Announce Type: new Abstract: Learning dense correspondences across deformable 3D shapes remains a long-standing challenge due to structural variability, non-isometric deformation, a
arXiv:2507.22041v2 Announce Type: replace Abstract: Deep learning has witnessed the extensive utilization across a wide spectrum of domains, including fine-grained few-shot learning (FGFSL) which heav
arXiv:2605.18468v1 Announce Type: cross Abstract: We study approximation by shallow ReLU^s networks, sigma_s(t)=max{0,t}^s, and the generalization behavior of such networks under ell_1 path-norm contr
arXiv:2512.17843v4 Announce Type: replace-cross Abstract: By evaluating Large Language Models (LLMs) through uniform, text-only interfaces, current academic benchmarks obscure how the unique designs a
arXiv:2605.17999v1 Announce Type: new Abstract: This paper proposes a Shared Backbone Proximal Policy Optimization (Shared Backbone PPO) algorithm. By sharing the base module between the Actor and Cri
arXiv:2605.16973v1 Announce Type: new Abstract: Domain generalization aims to enhance model robustness against unseen domains with embedding distribution shifts. While large-scale vision-language mode
arXiv:2508.15100v2 Announce Type: replace-cross Abstract: Distribution shift, a change in the statistical properties of data over time, poses a critical challenge for deep learning anomaly detection s
Shouldn’t this mean > 100b in charitable giving for effective altruism adjacent projects from Anthropic founders & team members alone? New blog post: The third wave of American philanthropy Hundreds o
This post appears to be a community prompt-sharing discussion where Swyx invites people to share their '/goal' prompts (likely system prompts or directives designed to optimize AI behavior toward spec
arXiv:2605.16311v1 Announce Type: new Abstract: Distributed training of large neural networks is bottlenecked by full-precision gradient communication and by coordinatewise optimizers that ignore the
arXiv:2512.04746v2 Announce Type: replace-cross Abstract: Extremely low-bit quantization is critical for efficiently deploying Large Language Models (LLMs), yet it often leads to severe performance de
arXiv:2605.17850v1 Announce Type: cross Abstract: iffusion-based generative models increasingly rely on inference-time guidance, adding a drift term or reweighting mixture of experts, to improve sampl
arXiv:2312.03798v2 Announce Type: replace Abstract: Single Image Reflection Removal (SIRR) in real-world images is a challenging task due to diverse image degradations occurring on the glass surface d
arXiv:2605.17341v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved remarkable success, yet their reliance on massive datasets and unintended memorization of training data ra
arXiv:2505.21893v3 Announce Type: replace-cross Abstract: Preference learning has garnered extensive attention as an effective technique for aligning diffusion models with human preferences in visual
arXiv:2605.18221v1 Announce Type: cross Abstract: Real-time magnetic resonance imaging (rtMRI) of speech production enables non-invasive visualization of dynamic vocal-tract motion and is valuable for
arXiv:2605.16842v1 Announce Type: new Abstract: Diffusion Multi-Modal Large Language Models (dMLLMs) are powerful for image generation, but optimizing them through reinforcement learning (RL) remains
arXiv:2605.16650v1 Announce Type: cross Abstract: Evaluating multi-turn dialogue systems remains challenging because response quality depends not only on the current prompt, but also on previously est
arXiv:2605.18693v1 Announce Type: new Abstract: As LLM agents are increasingly built around reusable skills, a central challenge is no longer only whether agents can use provided skills, but whether t
arXiv:2602.14211v2 Announce Type: replace-cross Abstract: Agent skills are increasingly used to extend LLM agents with task-specific instructions, executable scripts, and auxiliary resources. While im
arXiv:2605.16986v1 Announce Type: cross Abstract: LLM agents benefit from reusable skills, yet test-time tasks often require guidance more specific than a static skill library can provide. We propose
arXiv:2605.18401v1 Announce Type: cross Abstract: Long-horizon LLM agents leave traces that could become reusable experience, but raw trajectories are noisy and hard to govern. We treat Agent Skills a
arXiv:2605.16565v1 Announce Type: new Abstract: Skim is a speculative execution framework for web agents that exploits the predictable structure of purpose-built websites. Today's web-agent expense is
arXiv:2605.17949v1 Announce Type: new Abstract: Remote sensing vision-language models commonly rely on pretrained visual encoders to convert images into semantic features before language-model reasoni
arXiv:2605.16626v1 Announce Type: cross Abstract: Since autonomous coding agents generate complex behaviors at high-volume, we may want to use other LLMs to monitor actions to reduce the risk from dan
arXiv:2604.08432v2 Announce Type: replace-cross Abstract: Photonic neural networks promise ultrafast inference, yet most architectures rely on linear optical meshes with electronic nonlinearities, rei
Sneaky interventions, interactive installations, tools built for other artists to use. @kcimc's practice lives where machine learning, computer vision, and social technology collide. See his new inter
arXiv:2605.17842v1 Announce Type: new Abstract: Autoregressive language models execute Transformer layers sequentially, creating a latency bottleneck that is not removed by conventional tensor or pipe
Google is transitioning from the Gemini CLI tool to a new CLI called AGY (Antigravity CLI), but this change has drawbacks: AGY is not open source and no longer supports ACP functionality, representing
arXiv:2605.17423v1 Announce Type: new Abstract: We study series-level cinematic remaking, a long-horizon video-to-video generation problem that localizes full episodes or films via stylization or acto
arXiv:2605.17789v1 Announce Type: cross Abstract: Memory systems for AI assistants were built for single-user dialogue and fail characteristically when applied to multi-party social group settings. Th
Cybersecurity startup Sola Security Ltd. today announced the launch of Lumina, an autonomous risk intelligence platform that applies contextual artificial intelligence across cloud, identity, software
arXiv:2605.18232v1 Announce Type: cross Abstract: Somali is a Cushitic language of the Horn of Africa with ~25 million speakers, yet no documented dedicated Somali pretraining corpus with a companion
This X thread from Google AI showcases practical and creative applications of Gemini Omni, Google's multimodal AI model, as demonstrated and shared by the user community. The thread appears to be a cu
arXiv:2605.16872v1 Announce Type: cross Abstract: AI agents increasingly act consequentially in the real world. This creates a problem we call consequence reception: harm occurs, the producing system
arXiv:2605.17710v1 Announce Type: new Abstract: Although modern multilingual Automatic Speech Recognition (ASR) systems support several Nigerian languages, their performance consistently lags behind h
arXiv:2511.00392v2 Announce Type: replace-cross Abstract: Accurate 3D reconstruction in visually-degraded underwater environments remains a formidable challenge. Single-modality approaches are insuffi
Bloomberg: Sources: Chinese AI startup Moonshot told investors it would revamp its corporate structure to pave the way for a Hong Kong IPO and comply with Beijing's rules — Moonshot AI has informed it
Financial Times: Sources: Demis Hassabis was an angel investor in Anthropic; PitchBook and Dealroom: former DeepMind researchers founded 12+ companies since 2021, raising $14B+ — Demis Hassabis, the f
Bloomberg: Sources detail growing concerns inside SoftBank over Masayoshi Son's 60B+ bet on OpenAI, which some fear concentrates too much capital into a single company — With more than 60 billion comm
Nikkei Asia: Sources: Intel asks its leading PC partners, including those in the US, China, and Taiwan, to use more 18A CPUs, citing better supply than chips on older nodes — TAIPEI — Intel is urging
Bloomberg: Sources: SpaceX expects to proceed with its acquisition of Cursor 30 days after its public trading debut, which is expected to occur on June 12 — SpaceX expects to proceed with its acquisit
Anna Tong / Forbes: Sources: Zyphra, which trains and runs inference for its open-weight models on AMD hardware, is raising a 500M Series B at a valuation of at least 5B — The Series B round, which ch
arXiv:2511.16309v2 Announce Type: replace Abstract: Sparse autoencoders (SAEs) are used to analyze embeddings, but their role and practical value are debated. We propose a new perspective on SAEs by d
arXiv:2509.23068v2 Announce Type: replace-cross Abstract: Recent advances in deep learning highlight the need for personalized models that can learn from small samples, handle high-dimensional feature