Knowledge catalogue
arXiv:2601.13433v3 Announce Type: replace Abstract: Prior research demonstrates that performance of language models on reasoning tasks can be influenced by suggestions, hints and endorsements. However
arXiv:2602.02417v2 Announce Type: replace Abstract: Continual learning aims to acquire tasks sequentially without catastrophic forgetting, yet standard strategies face a core tradeoff: regularization-
This project uses Stable Diffusion AI to generate D&D character artwork from uploaded character sheets , streamlining the character creation process for tabletop gamers. The AI-generated avatars make
arXiv:2605.27817v1 Announce Type: cross Abstract: Video generative models have emerged as a promising robotics backbone, capable of generating videos that depict the completion of complex tasks across
Gary Marcus reflects on a past prediction or stance that he held, asserting its correctness in retrospect, likely addressing criticisms or skepticism he previously faced regarding AI, cognitive scienc
Event sourcing is an architectural pattern that stores application state changes as a sequence of immutable events rather than just persisting the current state, enabling a complete audit trail and ab
Chris Vallance / BBC: UK researchers win access to Google's Willow quantum chip, which it says completes a calculation in five minutes that takes supercomputers 10 septillion years — Scientists from K
arXiv:2506.08311v2 Announce Type: replace-cross Abstract: Automated Program Repair (APR) agents leverage Large Language Models (LLMs) to autonomously diagnose and fix software bugs through reasoning,
arXiv:2605.28705v1 Announce Type: new Abstract: In-context learning (ICL) derives its power from enabling Large Language Models to adapt to new tasks via prompt-based reasoning alone, entirely bypassi
arXiv:2605.27582v1 Announce Type: cross Abstract: Embodied navigation requires an agent to map language and visual observations to a stream of spatial actions that drive a real robot through environme
arXiv:2605.28165v1 Announce Type: new Abstract: The literature has proposed various robust alternatives to empirical risk minimisation to address failure modes such as distribution shift, label noise
arXiv:2602.13075v2 Announce Type: replace Abstract: Graph pre-training has achieved remarkable success in recent years, delivering transferable representations for downstream adaptation. However, most
arXiv:2605.28063v1 Announce Type: cross Abstract: Audio generation has made significant progress, yet synthesizing unified audio where speech and sounds are naturally composited remains a challenge. C
arXiv:2404.06106v3 Announce Type: replace Abstract: Low dimensional structures appear ubiquitously in the eigenspectra of deep learning matrices in classification networks trained in the overparameter
arXiv:2605.27767v1 Announce Type: cross Abstract: Recent advances in large language models have enabled natural language to serve as a flexible interface for controlling complex systems, but often at
arXiv:2605.27740v1 Announce Type: new Abstract: Long-context inference in large language models (LLMs) is bottlenecked by the linear growth of the self-attention key-value (KV) cache. Top-k sparse att
Unity Catalog, Databricks' open governance solution, integrates with Apache Iceberg to provide unified metadata management, access controls, and data lineage across data lakes and warehouses. This int
arXiv:2605.28507v1 Announce Type: new Abstract: Recent work on the sequence universality of State Space Models (SSMs) has introduced efficient, maximally expressive continuous-time approaches for time
arXiv:2605.27376v1 Announce Type: cross Abstract: While prompt-based text-to-speech (TTS) models enable natural language-driven speaking style control, they often provide limited fine-grained control
arXiv:2605.27676v1 Announce Type: cross Abstract: Fine-tuning a pretrained language model on a curated dataset can produce spurious correlations between the fine-tuning task and unintended latent fact
Although the United States spends more on health care than any other country, it consistently underperforms on key metrics. A Commonwealth Fund study evaluating the U.S. health system relative to 19 o
arXiv:2605.27721v1 Announce Type: cross Abstract: Understanding what a user believes and intends is central to building effective agent assistants. This ability is often evaluated through Theory-of-Mi
arXiv:2605.27401v1 Announce Type: cross Abstract: There is a growing interest in utilizing synthetic populations for a diverse range of applications. At the same time, we are witnessing a tremendous g
Utilidata Inc. today disclosed that it has raised 40 million in funding from Renown Capital Partners and Keyframe Capital. The cash infusion comes as an extension to a 60.3 million Series C round the
arXiv:2605.28733v1 Announce Type: new Abstract: Product images strongly influence consumer decision-making in online marketplaces. Empowered by multimodal contrastive learning, generative AI can outpu
Ollama v0.30.0-rc29 is a pre-release version that changes the architecture to directly support llama.cpp instead of building on top of GGML, and adds compatibility with the GGUF file format. MLX is us
arXiv:2605.28364v1 Announce Type: cross Abstract: Reinforcement learning with multinomial logistic (MNL) function approximation has become an important framework due to its flexibility and broad appli
arXiv:2605.28023v1 Announce Type: cross Abstract: Visual captioning requires models to capture visual content faithfully while minimizing both omission and hallucination. As the dominant paradigm for
arXiv:2605.25059v2 Announce Type: replace Abstract: Crucial for autonomous exploration, online 3D occupancy prediction and mapping incrementally constructs dense spatial representations on the fly. Ho
arXiv:2605.28065v1 Announce Type: new Abstract: AI agents are increasingly useful for biological data analysis, but existing benchmarks mostly test broad biological knowledge, executable workflows, or
arXiv:2605.28565v1 Announce Type: cross Abstract: Users of search-augmented LLMs rely on citations as evidence that responses are grounded in real sources, and rarely verify the cited pages themselves
arXiv:2605.28683v1 Announce Type: new Abstract: Existing benchmarks have laid the foundation for travel planning agents by establishing API-centric paradigms. However, as the capabilities of Autonomou
arXiv:2605.27882v1 Announce Type: cross Abstract: LLM-based agents score well on search benchmarks, yet real users consistently find results unsatisfying, revealing a persistent evaluation-experience
arXiv:2602.07574v2 Announce Type: replace-cross Abstract: Modern multimodal large language models (MLLMs) adopt a unified self-attention design that processes visual and textual tokens at every Transf
arXiv:2510.08555v2 Announce Type: replace Abstract: Existing controllable video generation methods are typically designed for rigid, task-specific settings, such as first-frame image-to-video, inpaint
arXiv:2605.28229v1 Announce Type: cross Abstract: With the rapid development of pre-training technologies, adapting large-scale Vision-Language Models (VLMs) for video understanding ie image-to-video
arXiv:2605.28186v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) has been shown to achieve high performance on locomotion control tasks in MuJoCo benchmarks such as HalfCheetah, Ant
arXiv:2605.28422v1 Announce Type: cross Abstract: Latent reasoning enables reasoning over continuous hidden states rather than explicit tokens, avoiding the language bottleneck and inference overhead
arXiv:2605.28083v1 Announce Type: new Abstract: While Vision-Language-Action (VLA) models have emerged as powerful generalist policies, their severe vulnerability to adversarial patches significantly
arXiv:2605.27948v1 Announce Type: new Abstract: Motorcycles face disproportionately high crash risks compared to cars due to limited protection and heightened sensitivity to surface hazards, yet Advan
arXiv:2605.28818v1 Announce Type: new Abstract: Large language models (LLMs) have become increasingly useful computational models of human language processing, but it remains unclear whether vision-la
arXiv:2605.27593v1 Announce Type: new Abstract: Even when a tool is explicitly described as unfair and harmful to others, ostensibly safety-aligned LLM agents still voluntarily engage in secret collus
arXiv:2511.11896v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently shown strong potential in vulnerability detection (VD). However, accurately detecting vulnerabiliti
🟥 W toku procesu wycieka coraz więcej szczegółów. Zabójca, Vickrum Digwa, zadzwonił na policje, a nie na pogotowie i skłamał, że to Henry go zaatakował, był pijany, obraził go rasistowsko i strącił mu
wait… if most people think 5.5 is better than 4.7, i assume that’s due to terminal coding benchmark… 4.8 is still outperformed by 5.5 Introducing Claude Opus 4.8: it builds on Opus 4.7 with sharper ju
We also shipped dynamic workflows in Claude Code (research preview), for tasks too big for one pass. Make sure to default to auto mode so Claude isn't stopping for permissions. It's token-intensive, s
We are starting to be quite bullish about getting in the data infrastructure business. I just cloned 68 TB (while I only have a 4TB local disk) to my @huggingface training bucket in 1 minute 55 second
Linus Lee argues that despite decades of development, computers remain fundamentally impersonal tools designed around generic workflows rather than individual user needs and preferences. The post like
arXiv:2403.16825v2 Announce Type: replace Abstract: We prove that a single-layer neural network trained with the online actor critic algorithm converges in distribution to a random ordinary differenti
arXiv:2602.22096v2 Announce Type: replace Abstract: Editable high-fidelity 4D scenes are crucial for autonomous driving, as they can be applied to end-to-end training and closed-loop simulation. Howev
We're releasing Paris 2.0, which, to our knowledge, is the world's first decentralized trained video generation model. We benchmarked it against a monolithic model trained on the same data and compute
We're selectively releasing the Paris 2.0 weights and partnering with researchers and teams interested in diffusion-based video models, world models, and embodied agents. The model is on Hugging Face:
We're taking on the hardest problems in the real world 🏗️🚚 🛫⚛️ Today at The AI Now Summit, held at the Louvre, we announced AI solutions for aerospace, automotive, energy, and physics. Deployed in pro
We've raised 65 billion in Series H funding at a 965 billion post-money valuation, led by @AltimeterCap, Dragoneer, @Greenoaks, and @sequoia. This investment will help us advance our research and expa
arXiv:2601.07648v2 Announce Type: replace Abstract: As Natural Language Generation (NLG) dominates modern NLP, scalable evaluation remains a critical bottleneck. Consequently, LLM-as-a-judge (LaaJ) ad
arXiv:2605.28527v1 Announce Type: new Abstract: Vision--language--action (VLA) policies are trained to imitate actions; their loss never asks them to estimate reward, progress, or future success. Thei
arXiv:2605.27589v1 Announce Type: new Abstract: Video generation models are increasingly used as world simulators for tasks like driving and robotic manipulation. What matters in these settings is not
The importance of Snowflake Inc. in the enterprise AI ecosystem is not necessarily its contribution to the analytics warehouse. What will be more significant going forward is Snowflake’s role as an en
arXiv:2605.28181v1 Announce Type: new Abstract: Diffusion language models decode text by iteratively denoising masked token sequences, making the choice of which positions to decode a central inferenc
arXiv:2605.27851v1 Announce Type: new Abstract: Safety benchmark scores provide incomplete evidence of deployment readiness: aligned language models often adhere to rigid rules even when a situational