Knowledge catalogue
arXiv:2605.31547v1 Announce Type: new Abstract: Dynamical systems reconstruction (DSR) aims to learn surrogate models that capture the dynamics underlying time-series data. Reliably deploying these su
arXiv:2605.30600v1 Announce Type: new Abstract: Randomized sketching is a central tool for compressing large-scale optimization problems while preserving accuracy. In particular, sketches that are bas
arXiv:2605.30888v1 Announce Type: new Abstract: Building strong reward models (RMs) for language model alignment is bottlenecked by the cost and difficulty of acquiring diverse and reliable preference
AI agents possess incredible reasoning capabilities and can perform increasingly complex actions. But the reliability of agentic outcomes depends entirely on the quality of the context they can access
The gains are most obvious in coding and operational areas. Even conservative organizations are adopting coding agents fast. That doesn't mean AI adoption doesn't come with huge challenges and cost co
arXiv:2602.01186v2 Announce Type: replace-cross Abstract: Classical Federated Learning relies on a multi-round iterative process of model exchange and aggregation between server and clients, with high
arXiv:2605.30831v1 Announce Type: cross Abstract: Activity cliffs, structurally similar compounds with large potency differences, are widely treated as intrinsic features of chemical datasets. We argu
arXiv:2603.00068v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) systems impose substantial and growing environmental costs, yet transparency about these impacts has declined eve
arXiv:2602.04031v2 Announce Type: replace Abstract: Tabular Language Models (TLMs) have been claimed to achieve strong generalization for tabular prediction. We conduct a systematic re-evaluation of T
arXiv:2605.30389v1 Announce Type: cross Abstract: Pattern languages are a classical model in formal language theory and algorithmic learning theory. This note formulates the problem of computing the i
This article discusses how prefix-aware routing and prefix caching techniques can reduce the computational overhead and costs associated with running large language models at scale by eliminating redu
arXiv:2602.15293v2 Announce Type: replace-cross Abstract: This paper concerns the question of how AI systems encode semantic structure into the geometric structure of their representation spaces. The
arXiv:2605.31363v1 Announce Type: new Abstract: Many languages are written in multiple scripts, requiring large language models (LLMs) to generate equivalent linguistic content in distinct orthographi
arXiv:2605.30537v1 Announce Type: new Abstract: Data selection is increasingly used to reduce the cost of large language model (LLM) fine-tuning, with recent methods prioritizing samples by current ut
The OpenAI Foundation is doing a lot of wonderful things. Helping society become resilient to AI is going to be incredibly important. Much more to come here! AI is advancing quickly. Society’s ability
arXiv:2601.02380v4 Announce Type: replace-cross Abstract: Recent reports claim that Large Language Models (LLMs) have achieved the ability to derive new science and exhibit human-level general intelli
arXiv:2605.31192v1 Announce Type: new Abstract: Recently, thanks to the advent of Multimodal-LLMs, deepfake detectors are striving not only to be generalizable but also interpretable. We propose that
arXiv:2509.23195v2 Announce Type: replace Abstract: The hierarchical syntactic structure and non-hierarchical, statistical, or sequential factors have long been framed as rival theories in accounting
Elon Musk shared observations about the current state of artificial intelligence development and capabilities on X (formerly Twitter). The post likely discusses recent AI advances, challenges, or Musk
arXiv:2512.05038v2 Announce Type: replace Abstract: Concept vectors aim to enhance model interpretability by linking internal representations with human-understandable semantics, but their practical u
arXiv:2605.30454v1 Announce Type: cross Abstract: Tool-augmented LLM agents are vulnerable to prompt injection: a third party who controls part of the agent's context can plant instructions that the a
arXiv:2605.31404v1 Announce Type: cross Abstract: Large Language Model (LLM)-based navigation systems commonly construct explicit spatial representations (e.g., topological graphs, semantic raster map
“The technology worked. The value didn’t arrive,” Bain concluded in the report. https://www.bloomberg.com/news/newsletters/2026-06-01/bain-survey-ai-delivers-less-cost-reduction-than-many-firms-predic
arXiv:2605.31289v1 Announce Type: cross Abstract: Representation learning is a powerful tool for spatio-temporal abstraction within reinforcement learning (RL). Two well established approaches are thr
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