Knowledge catalogue
arXiv:2603.18532v3 Announce Type: replace-cross Abstract: The strong performance of large vision-language models (VLMs) trained with reinforcement learning (RL) has motivated similar approaches for fi
arXiv:2609.23263v1 Announce Type: new Abstract: Temporal logic is a formal language for reasoning about system behaviors over time. Signal temporal logic (STL), in particular, has been used to encode
arXiv:2609.22209v1 Announce Type: new Abstract: Empirical legal research often relies on turning research questions into structured data extracted from large collections of rulings and judgments. Desi
arXiv:2609.22213v1 Announce Type: new Abstract: Temporal Knowledge Graph Question Answering (TKGQA) requires answer inference from evidence that is both structurally valid and temporally admissible. E
arXiv:2607.09175v2 Announce Type: replace-cross Abstract: Deployed LLM agents rely on agentic context, the model-external textual control content assembled by an operational harness. In this work, the
arXiv:2609.22174v1 Announce Type: new Abstract: Anticipating emerging research directions is a critical goal of AI-assisted science. Existing methods mainly predict which concepts will co-occur in fut
arXiv:2609.22897v1 Announce Type: new Abstract: Large vision-language models (VLMs) enable recognition beyond a fixed class set, but their computational demands prevent them from running on many edge
arXiv:2603.26995v2 Announce Type: replace Abstract: Autonomous robots commonly aim to achieve a nominal objective while minimizing a cost. Without contingency preparation, this can leave them vulnerab
arXiv:2609.23275v1 Announce Type: new Abstract: Vision-language-action (VLA) policies increasingly incorporate structured intermediate supervision beyond action labels. Yet specifying what an intermed
arXiv:2609.23206v1 Announce Type: cross Abstract: Green's function based operator approximation offers an efficient route for solving linear partial differential equations under varying boundary condi
arXiv:2609.24864v1 Announce Type: new Abstract: Reaching a 6-DoF grasp pose in clutter requires a collision-free trajectory, conventionally obtained by reconstructing the scene in 3D and planning insi
arXiv:2609.23113v1 Announce Type: new Abstract: Foundation models (FMs) have expanded task and motion planning (TAMP) to manipulation problems specified through language and visual observations. Howev
arXiv:2607.11498v2 Announce Type: replace Abstract: Vision-language-action (VLA) models require 3D spatial reasoning, yet RGB observations encode robot-object geometry only implicitly. Lifting depth w
arXiv:2606.13279v2 Announce Type: replace Abstract: In bimanual robotic manipulation, task-relevant visual information varies with the task stage and context, while the interaction of the two arms shi
arXiv:2609.22588v1 Announce Type: new Abstract: Vision-language models (VLMs) perform strongly on visual question answering benchmarks, yet often make decisions that contradict visual evidence they ha
arXiv:2609.22234v1 Announce Type: new Abstract: Instruction hierarchy (IH) alignment teaches language models to prioritize higher-level instructions when inputs conflict. While studied primarily in te
arXiv:2609.22192v1 Announce Type: new Abstract: Heterogeneous multivariate time-series systems exhibit segment-specific nonlinear dynamics that challenge monolithic forecasting architectures. We propo
arXiv:2609.23131v1 Announce Type: new Abstract: Language-guided object retrieval under partial observability requires deciding whether to gather more evidence, interact with the scene, grasp a candida
arXiv:2609.22486v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly rely on external sources when answering questions that require proprietary information or up-to-date live we
arXiv:2609.23425v1 Announce Type: new Abstract: Computational Fluid Dynamics (CFD) is widely used to evaluate ventilation and contaminant transport in occupied buildings, but deployment at scale is li
arXiv:2602.24208v2 Announce Type: replace Abstract: Diffusion models achieve state-of-the-art video generation quality, but their inference remains expensive due to the large number of sequential deno
arXiv:2505.14468v2 Announce Type: replace Abstract: Multi-LoRA (Low-Rank Adaptation) serving allows many specialized LLM variants to share the same base model by attaching lightweight adapters. This m
arXiv:2609.23548v1 Announce Type: new Abstract: Generating sewing patterns from images and text requires modeling a heterogeneous representation composed of discrete topology and continuous geometry.
arXiv:2410.17021v2 Announce Type: replace Abstract: Large Language Models with chain-of-thought prompting, such as OpenAI-o1, have shown impressive capabilities in natural language inference tasks. Ho
arXiv:2609.22677v1 Announce Type: new Abstract: Lightweight and slim manipulators enable safe operation in human living environments. Proximal actuation using remote transmission mechanisms, such as w
arXiv:2609.24003v1 Announce Type: new Abstract: Text-controlled time series generation aims to synthesize sequences that follow natural-language descriptions while remaining faithful to real data dist
arXiv:2609.23305v1 Announce Type: new Abstract: Manipulation under time constraints requires both accurate actions and an execution rhythm that matches the evolving scene. This becomes critical when a
arXiv:2606.14071v2 Announce Type: replace Abstract: We propose ShearFuse-UNet, a lightweight and computationally efficient deep learning model for next-day wildfire spread prediction from multi-modal
arXiv:2609.23164v1 Announce Type: cross Abstract: Vinyl restoration systems must distinguish isolated clicks, short bursts, dense crackle, and overlapping damage before selecting a repair operation. W
arXiv:2609.22991v1 Announce Type: cross Abstract: Apple Silicon machines with 192GB or more of unified memory make it routine to place tensors with more than 2^{32} elements on a desktop GPU. We show
arXiv:2507.00236v4 Announce Type: replace Abstract: Simulation-based design, optimization, and validation of autonomous vehicles have proven to be crucial for their improvement over the years. Neverth
arXiv:2609.23995v1 Announce Type: new Abstract: Linear models with an L_1-norm penalty remain state-of-the-art for high-dimensional (d > 1,000,000) tasks, offering a straightforward method for solving
Our most recent work at Templar explores fault tolerance in Crucible, our distributed pre-training platform. The goal is to keep healthy workers training when another pipeline stage goes offline. Cruc
arXiv:2609.22630v1 Announce Type: new Abstract: Subjective user experience is important to human-robot interaction, but the outcomes users value, and how those preferences vary across individuals and
arXiv:2508.01661v2 Announce Type: replace Abstract: Amodal segmentation aims to recover complete object shapes, including occluded regions, serving as an essential technique for user-centric multimedi
arXiv:2609.24198v1 Announce Type: cross Abstract: This paper describes the SKstars submission to SHROOM-Visions 2026, a shared task on fine-grained hallucination detection in large vision-language mod
arXiv:2609.24894v1 Announce Type: cross Abstract: Whole-slide pathology images (WSIs) contain gigapixel-scale visual content, creating a major scalability challenge for slide-level multimodal large la
arXiv:2601.01352v2 Announce Type: replace Abstract: Human identity-preserving text-to-video generation remains challenging under large changes in viewpoint, facial expression, illumination, and motion
arXiv:2601.13519v4 Announce Type: replace-cross Abstract: This paper introduces a new problem-dependent regret measure for online convex optimization with smooth losses. The notion, which we call the
arXiv:2603.14598v2 Announce Type: replace Abstract: Microgravity rendezvous and close proximity operations (RPO) is a growing area of interest for applications spanning in-space assembly and manufactu
arXiv:2609.23456v1 Announce Type: new Abstract: High-precision positioning using the global navigation satellite system (GNSS) embedded in smartphones is demanded for sidewalk-level pedestrian navigat
arXiv:2609.22854v1 Announce Type: cross Abstract: Vision-language-action models often predict actions from only the current observation, which can leave tasks involving object occlusion or visually id
arXiv:2609.24552v1 Announce Type: new Abstract: Embodied AI systems, particularly humanoid robots deployed in real world scenarios require whole-body control policies that are both task-responsive and
Krystal Hu / Reuters: Snorkel AI, which offers an “agentic data development platform” with humans and AI agents to create and vet data, raised 350M at a 3.5B valuation — Data startup Snorkel AI has ra
Tibo said Tuesday, GPT-6 Sol is suddenly everywhere, and now Claude Opus 5.5 leaks are blowing up too. Yet… nothing so far. 😂 At this point I’m just refreshing X like it’s a live event. What do you th
arXiv:2609.24911v1 Announce Type: new Abstract: Social simulation offers the social sciences an experimental instrument that the real world cannot supply, and generative agents have transformed it by
arXiv:2609.23239v1 Announce Type: new Abstract: An automated fact-checking system returns a label: the claim is true, or it is false. In many such systems the verdict remains the primary output. What
arXiv:2609.22126v1 Announce Type: cross Abstract: High-resolution surface solar radiation (SSR) is important for solar forecasting and grid operation. However, physically consistent reanalysis product
arXiv:2609.23019v1 Announce Type: cross Abstract: Soma instance segmentation, i.e., identifying and delineating individual cell somas as distinct instances, is crucial for cellular analysis and connec
arXiv:2609.23955v1 Announce Type: new Abstract: Previous work on Egyptian Arabic in NLP has focused largely on the prestigious Cairene Egyptian Arabic (CEA) dialect, resulting in a lack of representat
Anna Tong / Forbes: Sources: AI training data startup Micro1 raised 100M+ at a 4B valuation, up from 500M in September 2025 — At the beginning of last year, Ali Ansari's company, Micro1, was a recruit
Bloomberg: Sources: Mirendil, founded by former Anthropic researchers to build self-improving AI, is in talks to raise ~1B led by Kleiner Perkins at a 5B valuation — Mirendil, an artificial intelligen
arXiv:2609.23248v1 Announce Type: new Abstract: A fundamental challenge in deploying vision models is domain shift, which arises when training and test data follow different distributions, leading to
arXiv:2609.23153v1 Announce Type: new Abstract: Video diffusion transformers are expensive because attention dominates long spatiotemporal token sequences. We identify the high-sparsity trap: at extre
arXiv:2609.23937v1 Announce Type: cross Abstract: Robust linear fits can resist response contamination yet remain too dense or unstable for useful global explanations. We propose penalized distillatio
arXiv:2609.24708v1 Announce Type: new Abstract: Robotic perception often requires solving large nonlinear least-squares (NLS) problems. While sparsity has been widely exploited to scale solvers, a com
arXiv:2609.24470v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly explored as interfaces for scientific image analysis, where a visual question-answering (VQA)
arXiv:2609.23038v1 Announce Type: cross Abstract: Spatial reasoning is essential for vision-language models (VLMs) to understand and act in the physical world. Reasoning in dynamic environments requir
arXiv:2609.22479v1 Announce Type: new Abstract: We address the problem of recovering high-speed videos from dynamic scenes under extreme photon sparsity. Existing methods rely on aggregating photon de
arXiv:2609.24111v1 Announce Type: cross Abstract: Test-time adaptation (TTA) addresses distribution shift using only unlabeled test data. Existing methods typically adapt pretrained models by updating