Knowledge catalogue
arXiv:2609.18620v1 Announce Type: new Abstract: Creating deformable assets for robot manipulation requires jointly specifying their geometry, appearance, and physical properties. This is especially ch
arXiv:2609.18943v1 Announce Type: cross Abstract: Reducing radiation dose in computed tomography significantly degrades image quality and poses challenges for accurate and clinically reliable reconstr
arXiv:2609.18634v1 Announce Type: cross Abstract: Video streaming dominates global internet traffic, yet conventional pipelines remain inefficient for structured, human-centric content such as sports,
Hi Ollama Team, I’m writing regarding the announced retirement of GLM-5.1 from Ollama Cloud on 25 September 2026. I wanted to provide some fairly detailed technical feedback because GLM-5.1 is not sim
arXiv:2609.16519v1 Announce Type: new Abstract: Scientific research increasingly relies on large, heterogeneous data sources, motivating interest in retrieval-augmented generation (RAG) systems that p
arXiv:2609.16213v1 Announce Type: new Abstract: Artificial intelligence is reshaping biological research across an increasingly connected digital-to-physical workflow. General-purpose large language m
arXiv:2609.17106v1 Announce Type: new Abstract: Detecting and grasping small objects remains a significant challenge in robotics. Active vision, where the robot moves closer to the object, is an intui
arXiv:2508.15774v2 Announce Type: replace Abstract: Visual diffusion models achieve remarkable progress, yet they are typically trained at limited resolutions due to the lack of high-resolution data a
arXiv:2609.15996v1 Announce Type: new Abstract: Chen, Zhao, and Cohan introduce a valuable distributional evaluation of LLM-generated research ideas. This comment raises a narrower identification conc
arXiv:2609.16768v1 Announce Type: new Abstract: IMU-based human activity recognition (HAR) enables continuous, privacy-friendly monitoring of daily activities using wearable sensors. However, building
arXiv:2609.16344v1 Announce Type: cross Abstract: Sustained emotional support is a long-horizon interaction task closely tied to human well-being. Recent research demonstrates generative agents' capac
arXiv:2609.17326v1 Announce Type: new Abstract: Scientific poster generation distills a multimodal paper into a single-page visual artifact, forcing strict trade-offs between informational coverage an
arXiv:2609.17430v1 Announce Type: new Abstract: Hybrid dynamical systems provide a powerful modeling framework for robotic systems, particularly in contact-rich environments. However, ensuring safety
arXiv:2609.17088v1 Announce Type: new Abstract: Recent advancements in large language models have significantly enhanced the capabilities of agents in modeling long-term conversations. Despite these s
arXiv:2609.17509v1 Announce Type: cross Abstract: Neural audio codecs are a key component in speech language modeling. However, their high frame rates lead to long sequence lengths, increasing computa
arXiv:2609.16245v1 Announce Type: new Abstract: Long-horizon scientific discovery requires agents to alternate between exploration, disciplined execution, and critical reassessment as evidence changes
arXiv:2609.16090v1 Announce Type: cross Abstract: Music retrieval is relation-dependent: given a reference track, a listener may seek its style with a new theme, a cover, or a comparable voice, and th
arXiv:2609.17521v1 Announce Type: cross Abstract: Interactive control for video generation is moving from coarse prompts toward fine-grained, physically meaningful manipulation of dynamic scenes. Yet
arXiv:2609.16527v1 Announce Type: cross Abstract: Exploring the chemical space of flexible molecules remains challenging because the vast number of possible compounds and conformations, together with
arXiv:2609.17440v1 Announce Type: new Abstract: Optimizing industrial process flowsheets is often computationally prohibitive due to the high cost of rigorous simulations and the curse of dimensionali
arXiv:2609.16660v1 Announce Type: new Abstract: Test-time reinforcement learning adapts a model on its own unlabeled test set using majority-vote pseudo-labels and has shown strong results in mathemat
arXiv:2512.05126v2 Announce Type: replace-cross Abstract: Automatic video dubbing aims to generate high-fidelity speech that is temporally aligned with visual content. However, existing methods still
I wanted to test what Qwen 3.8 27B running locally on a single 5090 could do in Row-Bot. I gave it just one prompt: 'I want you to create an animation showing what the current local model can do. Test
arXiv:2609.16705v1 Announce Type: new Abstract: Physical AI requires more than increasingly large robot datasets: intelligent robots acquire knowledge through continuous interaction with the physical
arXiv:2609.16232v1 Announce Type: new Abstract: Geospatial artificial intelligence (GeoAI) powered by large language models (LLMs) is expanding the capacity to query, generate, and interpret spatial i
arXiv:2408.15538v4 Announce Type: replace Abstract: While modern Autonomous Vehicle (AV) systems can develop reliable driving policies under regular traffic conditions, they frequently struggle with s
arXiv:2609.13168v1 Announce Type: cross Abstract: Speech AI, any AI system that recognizes, transforms, or generates speech, is built and evaluated across two communities with only a small overlap: te
arXiv:2609.14462v1 Announce Type: new Abstract: Interactive video world models must maintain broad scene context under camera motion while producing high-fidelity observations with low latency. Existi
arXiv:2609.13869v1 Announce Type: cross Abstract: Automatic sentence function identification is important for many downstream natural language processing (NLP) applications such as dialogue systems, t
arXiv:2609.13345v1 Announce Type: cross Abstract: Probabilistic forecasting is central to decision-making under uncertainty, yet its methodological landscape has become increasingly fragmented across
arXiv:2609.15478v1 Announce Type: new Abstract: Multimodal agents can create complex videos in software such as Blender by coding without relying on diffusion models. Yet video understanding benchmark
arXiv:2609.15393v1 Announce Type: cross Abstract: Text-to-Time Series Generation (Text-to-TS) provides a promising paradigm for synthesizing time series from natural language, enabling scenario-specif
arXiv:2609.14642v1 Announce Type: new Abstract: Generation of musculoskeletal gait trajectories conditioned on patient-specific parameters remains a key challenge for wearable robotics and rehabilitat
arXiv:2609.14408v1 Announce Type: new Abstract: We present an automated pipeline that converts NCERT textbooks into interactive video explanations that respond directly to user queries. A user uploads
arXiv:2609.15392v1 Announce Type: cross Abstract: Recent progress in image and 3D scene generation has enabled increasingly realistic static environments, yet most methods remain confined to such stat
arXiv:2609.15209v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) improves language-model programs by revising prompts from task feedback, yet it typically holds its training data
arXiv:2511.12101v3 Announce Type: replace-cross Abstract: Many recent Vision-Language-Action models employ diffusion or flow-matching backbones with hundreds of millions of parameters for action gener
arXiv:2609.14761v1 Announce Type: cross Abstract: Visual feedback in the form of user-uploaded images and videos is becoming increasingly common in e-commerce platforms because it provides authentic e
arXiv:2609.14779v1 Announce Type: new Abstract: Performing deliberate mathematical reasoning in visual contexts is a hallmark of advanced Multimodal Large Language Models (MLLMs) and requires a sophis
arXiv:2609.15018v1 Announce Type: new Abstract: We study relative position encoding for multi-view vision Transformers under camera heterogeneity, including varying fields of view (FoVs) or projection
The NVIDIA Vera Rubin platform attains superior performance‑per‑watt by combining factory‑level DSX MaxLPS power shifting, rack‑level capacitors with Intelligent Power Smoothing, and the Groq 3 LPX de
arXiv:2609.15859v1 Announce Type: new Abstract: Extracting informative representations from longitudinal data that can predict future outcomes remains a critical challenge in medicine. Medical dataset
arXiv:2603.02504v3 Announce Type: replace Abstract: Large Language Models (LLMs) achieve strong performance on natural language tasks but remain unreliable in mathematical reasoning, frequently genera
arXiv:2609.15695v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly power consumer-facing AI search, yet evaluating them on the diversity of everyday visual questions remains ch
arXiv:2609.13291v1 Announce Type: cross Abstract: We present ScorePrompts, an interactive system in which users upload a score, receive natural-language descriptions of its musical structure, ask ques
arXiv:2609.14882v1 Announce Type: cross Abstract: Nucleotide sequence analysis is central to problems spanning regulatory genomics, evolutionary biology, and phenotype prediction. Classical bioinforma
arXiv:2609.15857v1 Announce Type: new Abstract: This paper establishes a perfect-reconstruction (PR) interpretation of AddUNet and its full-rate realization, and introduces a Residual Full-Rate PR arc
arXiv:2603.02720v2 Announce Type: replace Abstract: Recently, tensor decompositions have attracted increasing attention. Fundamentally, different interactions among factors induce distinct tensor deco
arXiv:2609.14124v1 Announce Type: cross Abstract: Medical image analysis is often hindered by biased datasets, which can lead to biased models and limited clinical applicability. A promising strategy
arXiv:2603.15159v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown strong potential for code generation, yet they remain limited in private-library-oriented code generat
arXiv:2602.21061v2 Announce Type: replace Abstract: Many current paths to more advanced AI depend on the assumption that large language models (LLMs) can generalize learned relationships to solve comp
arXiv:2609.14168v1 Announce Type: cross Abstract: Context parameterization enables large language models (LLMs) to internalize contexts into reusable model parameters, avoiding repeated processing acr
arXiv:2603.25165v3 Announce Type: replace Abstract: Recent advances in self-supervised learning (SSL) for point clouds have substantially improved 3D scene understanding without human annotations. Exi
arXiv:2609.15834v1 Announce Type: new Abstract: Detector response nonuniformity introduces systematic projection errors and ring artifacts in photon-counting detector computed tomography (PCD-CT). In
arXiv:2609.13294v1 Announce Type: new Abstract: Converting scientific graphics into editable representations remains a challenging problem for image-to-code generation because of their heterogeneous e
arXiv:2609.13348v1 Announce Type: cross Abstract: This paper presents ViFA-Council, a three-stage multi-agent framework that employs multiple large language models (LLMs) to tackle two culturally comp
arXiv:2609.14500v1 Announce Type: new Abstract: AI scaling studies increasingly evaluate systems that combine a pretrained model with retrieval, search, verification, tools, and interaction. Yet a hig
arXiv:2609.12830v1 Announce Type: new Abstract: Continuous emotion control in text-to-image generation requires a model to improve affective alignment without changing the objects, layout, or scene de
arXiv:2609.13047v1 Announce Type: cross Abstract: Humans organize knowledge into a taxonomy of concepts with nested levels of abstraction and a basic level at which people recognize and name objects w
arXiv:2609.12872v1 Announce Type: new Abstract: We present DuplexDrama, the first synthesized spoken dialogue dataset that simultaneously covers four dimensions: (i) complete persona and scenario sett