Knowledge catalogue
TL;DR - A ~4M example, ~3B token CoT dataset designed around helping small models think more concisely, accurately and reliably. Hi all! For the past few months I have been working on a dataset design
arXiv:2608.21700v1 Announce Type: cross Abstract: Continuous-time flow and diffusion models are widely used across many application domains, from large-scale deployment in computer vision and protein
arXiv:2608.22597v1 Announce Type: cross Abstract: Subsampling is effective in tackling computational challenges for massive data with rare events. Overly aggressive subsampling may adversely affect es
arXiv:2608.22549v1 Announce Type: new Abstract: Batched simulators for autonomous driving have recently enabled training reinforcement learning (RL) agents at scale, encompassing thousands of traffic
arXiv:2506.00209v3 Announce Type: replace-cross Abstract: Population health management requires scalable methods to identify individuals at risk of chronic diseases such as cardiovascular conditions a
arXiv:2606.16661v2 Announce Type: replace-cross Abstract: Fixed-length chunking in Retrieval-Augmented Generation (RAG) often leads to boundary fragmentation, where critical evidence is split across s
arXiv:2608.22390v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong potential in graphical user interface (GUI) generation, but reliable evaluation remains challengin
arXiv:2608.21375v1 Announce Type: new Abstract: Heterogeneous agentic retrieval-augmented generation (RAG) systems increasingly orchestrate external APIs, internal databases, vector stores, and graph
arXiv:2608.22802v1 Announce Type: cross Abstract: Medical large language models are often judged by how many clinical questions they answer correctly. That view is useful, but it misses a practical ri
arXiv:2608.22725v1 Announce Type: new Abstract: Short-drama generation has grown into a large, industrialized pipeline, and as it scales from isolated shots to the episode level, visual continuity has
arXiv:2608.22062v1 Announce Type: new Abstract: Longitudinal clinical event-relation verification determines whether a patient record supports a specified relation among two or more clinical events. T
arXiv:2608.21500v1 Announce Type: cross Abstract: Prompt injection is listed as the #1 threat to AI agents. When an agent accesses external data from websites, files, or emails, an attacker may inject
arXiv:2608.22740v1 Announce Type: new Abstract: Generalizable 3D Gaussian Splatting (G-3DGS) has emerged as a promising approach for novel view synthesis undersparse-view settings. However, existing f
arXiv:2506.13529v2 Announce Type: replace-cross Abstract: Seismic acoustic impedance plays a crucial role in lithological identification and subsurface structure interpretation. However, due to the in
arXiv:2608.21499v1 Announce Type: cross Abstract: Cardiac auscultation remains the most cost-effective screening procedure for cardiovascular diseases, and requires listening at the four main ausculta
arXiv:2608.21402v1 Announce Type: cross Abstract: World action models (WAMs) jointly denoise future video frames and robot actions, and the video prior is expected to generalize their control. Camera
arXiv:2608.22300v1 Announce Type: new Abstract: Co-registration underlies nearly every multi-temporal and multi-sensor use of optical satellite imagery, and operational products still carry documented
arXiv:2608.22387v1 Announce Type: cross Abstract: Wearable and smartphone-based emotion recognition (WER) remains a challenging setting in affective computing, due to the notorious difficulty and bias
arXiv:2608.22898v1 Announce Type: new Abstract: Diffusion language models (DLMs) alleviate the inherent latency bottleneck of autoregressive (AR) large language models (LLMs), but their degraded gener
arXiv:2608.21610v1 Announce Type: new Abstract: Retrieval-augmented generation relies mostly on flat, fixed-granularity indexes: documents are cut into uniform chunks and retrieved by similarity, disc
arXiv:2608.22090v1 Announce Type: cross Abstract: Large language models can produce fluent reasoning traces whose local semantic errors propagate to an incorrect conclusion, while unconstrained self-c
arXiv:2608.23249v1 Announce Type: new Abstract: We consider a multistatic radio-frequency imaging problem with anisotropy, in which the reflection from a point depends on the positions of the transmit
arXiv:2608.21636v1 Announce Type: new Abstract: Video Object-Centric Learning (OCL) has traditionally focused on refining the encoder architecture to ensure temporal consistency. In this paper, we arg
arXiv:2602.18699v2 Announce Type: replace-cross Abstract: Studies of semantic drift report heterogeneous signals, including embedding displacement, neighbor change, distributional divergence, and recu
arXiv:2608.22321v1 Announce Type: new Abstract: Multimodal time-series forecasting has emerged as a promising paradigm in which natural-language context is expected to improve predictive performance.
arXiv:2606.12849v2 Announce Type: replace-cross Abstract: Semantic mapping is a core service that enables grounded interactions in emerging Extended Reality (XR) applications such as AI assistants. De
arXiv:2501.06926v5 Announce Type: replace-cross Abstract: Double reinforcement learning (DRL) provides efficient off-policy inference for policy values in nonparametric Markov decision processes (MDPs
arXiv:2608.21599v1 Announce Type: cross Abstract: Voice has been proposed as a low-cost screening signal for chronic obstructive pulmonary disease (COPD). COPD is strongly age-associated and voice cha
arXiv:2608.23211v1 Announce Type: cross Abstract: In this work, we study the oracle complexity of finding an epsilon-stationary point for nonconvex-strongly-convex (NC-SC) bilevel optimization using o
arXiv:2608.23100v1 Announce Type: cross Abstract: Robot co-design via bi-level optimization couples within-lifetime controller learning for fitness evaluation with cross-generational morphological evo
arXiv:2608.22252v1 Announce Type: cross Abstract: We establish sharp Barron regularity for Coulombic many-electron wave functions after extraction of the universal cut-off Jastrow factors. Following t
arXiv:2603.11421v2 Announce Type: replace Abstract: Text-driven video generation has democratized film creation, but camera control in cinematic multi-shot scenarios remains a significant block. Impli
arXiv:2608.23296v1 Announce Type: cross Abstract: Learned KV-cache eviction often faces a soft-to-hard mismatch: during training, differentiable gates typically attenuate token contributions, whereas
arXiv:2608.23067v1 Announce Type: new Abstract: Agent Skills are reusable procedural modules that are increasingly injected into coding-agent sessions to encode framework conventions, anti-patterns, a
v4.5.0: Added native desktop control, agent execution budgets, concurrency limits, loop protection, and safer local embedding fallback. v4.6.0: Rebuilt agents around durable parent-led orchestration.
arXiv:2608.22965v1 Announce Type: new Abstract: Accurate extrinsic calibration between event-based and frame-based cameras remains a practical bottleneck for heterogeneous stereo systems. Existing app
Since announcing Jalapeño, our first custom inference chip, we’ve been testing it and the system around it. The results show a major advance: more intelligence from every watt and faster responses, de
arXiv:2608.22821v1 Announce Type: new Abstract: We present SiZeUp, a fast and scalable approach for constructing large-scale 3D urban proxy models directly from calibrated oblique aerial imagery. Our
arXiv:2608.21659v1 Announce Type: new Abstract: Vector sketches remain one of the most concise and immediate mediums for abstract human expression. However, generating high-quality vector strokes that
Skild AI: Skild AI unveils S1, a robotics foundation model that it says can learn tasks never seen during pretraining, using a single video demo, without fine-tuning — UNSEEN TASKS10-MINUTE HORIZONSON
arXiv:2608.23417v1 Announce Type: new Abstract: Agent skills are reusable procedural artifacts that extend language agents with specialized workflows, tool conventions, and domain behaviors at inferen
arXiv:2608.21929v1 Announce Type: cross Abstract: Agent skills extend coding agents with task-specific instructions, scripts, and resources, but they also create a trusted instruction channel that can
arXiv:2512.04529v3 Announce Type: replace Abstract: Creating presentation slides from scientific papers is not simply a matter of summarizing paragraphs. A presenter is required to decide what story t
arXiv:2510.00279v3 Announce Type: replace-cross Abstract: Logical rule-based methods offer an interpretable approach to knowledge graph completion (KGC) by capturing compositional relationships in the
arXiv:2607.15772v2 Announce Type: replace Abstract: Maintaining recurring character identities across scene transitions and long temporal gaps is a central challenge in narrative long video generation
arXiv:2608.11596v1 Announce Type: cross Abstract: Modern radar systems require adapting their processing strategies in response to changing interference, clutter, and data availability. This paper int
arXiv:2608.22472v1 Announce Type: new Abstract: Function calling represents the core capability of agentic large language models (LLMs). Existing research has focused on enhancing LLMs function-callin
arXiv:2608.21411v1 Announce Type: new Abstract: Forecasting pedestrian motion has always been fundamental for autonomous navigation in crowded environments. While attention-based methods achieve stron
arXiv:2405.01990v2 Announce Type: replace Abstract: PU learning refers to the classification problem in which only part of positive samples are labeled. Existing PU learning methods treat unlabeled sa
arXiv:2608.21449v1 Announce Type: new Abstract: Time series arise in a wide range of application domains and are analyzed using machine learning in decision-critical settings. Time series classificati
arXiv:2608.21579v1 Announce Type: new Abstract: Consider the following problem of learning an unknown linear order on n items. In each round, the learner guesses a complete ordering of the items and r
Corrie Driebusch / Wall Street Journal: Sources: Anthropic is likely to tell IPO investors that its potential revenue opportunities are above 30T, topping SpaceX's 28.5T; Uber predicted $6T in 2019 —
Anissa Gardizy / Wall Street Journal: Sources: Chris Malone, who joined OpenAI as head of data centers in March 2025, left the company last week amid a broader exodus — Chris Malone joins a string of
arXiv:2608.22018v1 Announce Type: new Abstract: Hate speech detection has recently shifted from coarse-grained classification to structured parsing, where systems must jointly identify hateful targets
arXiv:2608.22595v1 Announce Type: cross Abstract: We develop a new framework for flexible, nonlinear, and interpretable off-policy evaluation for infinite-horizon reinforcement learning. To handle lar
arXiv:2608.21948v1 Announce Type: new Abstract: Complex clinical reasoning requires models to update diagnostic hypotheses as new evidence emerges and to coordinate different medical specialities unde
arXiv:2608.21551v1 Announce Type: cross Abstract: Complex-valued arrays arise in signal processing, where scientific interpretation depends on retaining amplitude and phase information. Existing covar
arXiv:2608.21776v1 Announce Type: new Abstract: Recent advances in image editing allow impressive manipulation of objects, existing methods still struggle to handle spatial movement in complex scenes,
arXiv:2509.04719v3 Announce Type: replace-cross Abstract: The widespread adoption of diffusion models for image generation necessitates efficient parallel inference to manage their substantial computa
arXiv:2608.23279v1 Announce Type: new Abstract: Text-driven human motion synthesis has made substantial development with two core modules of motion representation and generative architecture. For repr