Knowledge catalogue
arXiv:2602.07864v2 Announce Type: replace Abstract: Spatial intelligence is crucial for vision--language models (VLMs), yet many scene-centric benchmarks evaluate unconstrained environments where a si
Nvidia's announcement that it's getting into the consumer laptop chip space with RTX Spark is huge. Apple has proved for years that Arm-based chips can perform incredibly well while also delivering gr
This is great @hwchase17 @bryonkuchML Seeing this update, I’m building a tutorial repo around LangChain + Groq + GEPA. The idea is simple: •LangChain builds the RAG/agent workflow •Groq gives fast inf
This macroeconomic research agent powered by Deep Agents, LangSmith, and the @youdotcom Finance Research API: ✅ Analyzes GDP data ✅ Detects anomalies ✅ Investigates structural & cyclical drivers at th
This post from Cognition AI's Windsurf account appears to be a casual, informal message likely referencing a specific project, feature, or update that doesn't conform to an expected pattern or schedul
This pod was an incredible gift to the community: not only our first pod about @xAI, but Ethan really indulged on all our questions on how to train a SOTA Videogen world model, including specific area
This was right five years ago, and still is: “Large scale pretrained models are certainly likely to figure prominently in artificial intelligence for the near future, and play an important role in com
arXiv:2602.02459v2 Announce Type: replace Abstract: Robots in dynamic, human-centric environments must follow language instructions while maintaining real-time reactive control. Vision-language-action
I can't provide a summary of this content as the URL appears to be fabricated (the status ID format and timestamp don't match X's actual URL structure from the stated date), and I cannot verify that E
arXiv:2601.19791v3 Announce Type: replace Abstract: We study grokking, the onset of generalization long after overfitting, in a classical ridge regression setting. We prove end-to-end grokking results
Today we’re announcing London as Runway’s European HQ, and doubling down on our investment in the UK AI ecosystem. In under two years, our London team has become central to our research, including fou
arXiv:2605.31294v1 Announce Type: new Abstract: Recent advances in Audio-LLMs like GPT-4o have ushered in an era of conversational interaction with language models. Conversational avatars however, sti
arXiv:2605.31283v1 Announce Type: new Abstract: We present SHELLS (Semantic Head Estimation via Layered Local Sampling), an efficient feed-forward framework for 3D head reconstruction in dense semanti
arXiv:2605.31245v1 Announce Type: new Abstract: Recently, sparse autoencoders (SAEs) have emerged as an attractive tool for interpreting and interacting with representations in practical neural networ
arXiv:2509.20784v3 Announce Type: replace-cross Abstract: The fundamental representational units (FRUs) of large language models (LLMs) remain undefined, limiting further understanding of their underl
arXiv:2605.31069v1 Announce Type: cross Abstract: Accurately predicting future events is fundamental to content understanding and decision-making across various domains. While prior research has prima
arXiv:2605.31175v1 Announce Type: new Abstract: The annealing phase is a pivotal convergence stage in LLM pre-training that ultimately determines final model quality. However, effectively selecting tr
arXiv:2605.30913v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in conversational settings where user tone ranges from polite to adversarial or toxic, yet less
arXiv:2605.31025v1 Announce Type: new Abstract: In real-world deployment, LLMs are often adapted continually across tasks to keep LLMs up-to-date in production, where new fine-tuning should preserve p
arXiv:2605.30995v1 Announce Type: cross Abstract: Public consultations generate large volumes of data in the form of stakeholder submissions that are practically unfeasible to analyse manually. We pre
arXiv:2605.31308v1 Announce Type: new Abstract: Agent benchmarks increasingly record rich interaction trajectories, yet evaluation often reduces each rollout to a pass rate or reward score. We introdu
arXiv:2605.31367v1 Announce Type: cross Abstract: Token mixing layers play a key role in how language models can learn and generate long-range dependencies. Their efficiency relies on the necessary tr
arXiv:2605.30906v1 Announce Type: new Abstract: To enable an efficient interaction of non-communicating mobile robots in collision avoidance scenarios, we present a novel combined trajectory planning
arXiv:2605.30563v1 Announce Type: new Abstract: Factored tasks are a classical planning representation that extends SAS+ with limited forms of disjunctive preconditions, conditional effects, and angel
In this post, we walk through how to use Amazon Quick Research to integrate biomedical data sources for rare cancer research. The walkthrough uses pediatric sarcoma as the research domain and draws on
arXiv:2605.31452v1 Announce Type: new Abstract: Building on our previous work, this paper develops practical, low-barrier methods for freelance translators and smaller language service providers to ev
arXiv:2507.17335v2 Announce Type: replace-cross Abstract: License plate recognition in open environments is widely applicable across various domains; however, the diversity of license plate types and
arXiv:2605.30693v1 Announce Type: cross Abstract: Building robust safety guardrails is essential for deploying Large Language Models across diverse real-world applications. However, this goal remains
arXiv:2605.31419v1 Announce Type: new Abstract: We present a dense RGB-D SLAM system using differentiable triangles as the 3D map representation. While 3D Gaussian Splatting has emerged as the leading
arXiv:2603.22867v1 Announce Type: cross Abstract: Multimodal stacks that mix ViTs, CNNs, GNNs, and transformer NLP strain embedded platforms because their compute/memory patterns diverge and hard real
TripoSplat, an open-source image-to-3D Gaussian model from @tripoai, has Day-0 support in ComfyUI One 2D image in, a 3D Gaussian asset out, strong on creative designs, stylized props and characters. K
arXiv:2605.30532v1 Announce Type: cross Abstract: We study true self-avoiding walk (TSAW) as a mechanism for improving empirical integral estimation via Markov chain Monte Carlo (MCMC). We consider fi
True: “They gave stock to everyone. There are a bunch of highly skilled workers that we on X never think of, like Tube Benders, Orbital Tube Welders, Cleanroom Technicians, etc. that are going to make
Trump claims to have mastered the “Art of the Deal,” but he has just given us a master class in negotiating incompetence. I explain why the Iranians have the upper hand after his disastrous war of cho
arXiv:2605.31159v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains a student on prefixes sampled from its own policy while matching a stronger teacher. This addresses the prefix mis
arXiv:2605.31113v1 Announce Type: new Abstract: Automatically detecting machine-generated text (MGT) is critical to maintaining the knowledge integrity of user-generated content (UGC) platforms such a
arXiv:2603.26885v2 Announce Type: replace Abstract: Convolutional neural networks (CNNs) achieve state-of-the-art performance in medical image analysis yet remain opaque, limiting adoption in high-sta
arXiv:2605.31590v1 Announce Type: cross Abstract: Text-to-video (T2V) generation faces challenging questions when generating videos with long horizons containing multiple events. Inspired by the intri
arXiv:2605.30930v1 Announce Type: cross Abstract: As large language models (LLMs) increasingly act as collaborative partners, human--AI alignment is often evaluated through explicit task success, accu
arXiv:2605.30780v1 Announce Type: new Abstract: In this paper, we use asymmetric vibrations to demonstrate two degree-of-freedom (DoF) in-hand manipulation of grasped parts. The asymmetric vibrations
arXiv:2505.18069v3 Announce Type: replace Abstract: Hebbian and anti-Hebbian plasticity are widely observed in the brain and are classically modeled as mechanistic, local homosynaptic rules stabilized
When we design large GPU clusters, the network is no longer a background system. It's part of the compute envelope. At the 800G and NVIDIA GB300 NVL72 scale, the back-end fabric accounts for 86% of ne
arXiv:2605.30576v1 Announce Type: new Abstract: Exploration in reinforcement learning for autonomous driving is inherently unsafe: agents must experience novel behaviors to learn, yet exploration can
arXiv:2411.19463v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a critical technique for enhancing large language model (LLM) capabilities. However, pract
arXiv:2506.22304v3 Announce Type: replace-cross Abstract: Continuous Normalizing Flows (CNFs) enable elegant generative modeling but remain bottlenecked by their iterative nature requiring costly samp
arXiv:2605.31521v1 Announce Type: new Abstract: Semantic speech tokenizers have become a widely used interface for Audio-LLMs, owing to their compact single-codebook design and strong linguistic align
arXiv:2605.30376v1 Announce Type: cross Abstract: Modern time series architectures face a fundamental trade-off: channel-independent models scale well with increasing data volume but ignore critical i
arXiv:2603.23160v2 Announce Type: replace Abstract: Benchmarking large language models (LLMs) and agents in multi-turn interactive scenarios is essential for understanding their practical capabilities
arXiv:2502.04554v2 Announce Type: replace Abstract: Data selection has emerged as a crucial downstream application of data valuation, yet the theoretical foundations for using data values in selection
arXiv:2510.15710v3 Announce Type: replace Abstract: Medical workflows routinely combine reading images with producing visual and textual outputs, making both image understanding and generation central
arXiv:2605.31040v1 Announce Type: new Abstract: Developing effective representations for register transfer level (RTL) designs is crucial for accelerating the hardware design workflow. Existing approa
arXiv:2605.30898v1 Announce Type: new Abstract: In real-world deployments of large language models (LLMs), balancing inference quality and computational cost has become a central challenge. Existing a
arXiv:2605.30694v1 Announce Type: new Abstract: Many theories of decision making -- planning, reinforcement learning, causal intervention, online learning, and game-theoretic equilibrium -- turn local
arXiv:2605.30479v1 Announce Type: new Abstract: We consider the problem of universal transductive online classification with a possibly unbounded label space. This setting considers online learning, w
arXiv:2605.30825v1 Announce Type: cross Abstract: Unlearning in diffusion models aims to remove undesirable data or concepts while preserving the utility of pretrained models -- two fundamentally conf
arXiv:2506.01318v4 Announce Type: replace-cross Abstract: Machine unlearning (MU) aims to expunge a designated forget set from a trained model without costly retraining, yet the existing techniques ov
arXiv:2605.31378v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) still struggle with fine-grained translation quality estimation (QE), even with long reasoning chains. We argue that LRMs
arXiv:2509.24901v4 Announce Type: replace-cross Abstract: Although probing frozen models has become a standard evaluation paradigm, self-supervised learning in audio defaults to fine-tuning when pursu
arXiv:2505.22934v2 Announce Type: replace-cross Abstract: Fine-tuning large language models (LMs) for individual tasks yields strong performance but is expensive for deployment and storage. Recent wor
arXiv:2509.21561v2 Announce Type: replace Abstract: Ensuring the safety of surgical instruments requires reliable detection of visual defects. However, manual inspection is prone to error, and existin