Knowledge catalogue
arXiv:2608.28568v1 Announce Type: new Abstract: Sign language production (SLP) aims to generate continuous signing motion from spoken language, often through gloss-to-pose generation. Prior work mainl
arXiv:2408.12831v2 Announce Type: replace Abstract: Current robotic manipulators require fast and efficient motion-planning algorithms to operate in cluttered environments. State-of-the-art sampling-b
arXiv:2606.20543v2 Announce Type: replace Abstract: Autoregressive image models treat images as 1D token sequences, inheriting the next-token factorization of language models. This flattening discards
arXiv:2608.28229v1 Announce Type: cross Abstract: Grammar-constrained decoding helps large language models produce syntactically valid structured outputs, such as code, JSON, and SQL. For context-free
arXiv:2509.19212v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in real-world applications, yet their ability to make context-aware safety decisi
arXiv:2608.28279v1 Announce Type: new Abstract: Multimodal lifelong navigation requires an agent to autonomously explore unseen environments while sequentially completing navigation tasks specified by
arXiv:2608.28467v1 Announce Type: new Abstract: Persona-based dialogue systems are usually conditioned on speaker biography, but dialogues involve at least two participants, and who has access to whos
arXiv:2607.15058v2 Announce Type: replace Abstract: CAD-to-image alignment aims to estimate an object's 9D pose (rotation, translation, and anisotropic scale) from a single RGB image, with application
arXiv:2509.24192v2 Announce Type: replace Abstract: Vision-language models (VLMs) have advanced multimodal perception, demonstrated by open-vocabulary object detection with simple language queries. St
arXiv:2608.28078v1 Announce Type: new Abstract: Vision foundation backbones provide strong representations for dense prediction, yet a single shared feature still needs to support tasks with different
arXiv:2608.27948v1 Announce Type: new Abstract: Test-time adaptation (TTA) on graphs aims to adapt a graph neural network (GNN) that is well-trained on the training graph to the test graph, which invo
arXiv:2608.27871v1 Announce Type: new Abstract: Long-video understanding remains challenging for Multimodal Large Language Models (MLLMs) due to limited context length. Uniform sampling may miss cruci
arXiv:2608.27612v1 Announce Type: cross Abstract: In neuroevolution, indirect encoding generates neural network connectivity from a compact genome rather than specifying each connection. ES-HyperNEAT
arXiv:2608.28524v1 Announce Type: new Abstract: Texture image classification plays a significant role in computer vision applications, including industrial inspection, medical image analysis, remote s
arXiv:2608.27750v1 Announce Type: cross Abstract: The hidden states of large language models (LLMs) are known to capture rich information relating to model knowledge and behavior that can be hard to e
arXiv:2606.17399v2 Announce Type: replace Abstract: When small transformers grok modular multiplication, prior work reports that the learned embedding has a 'dense' Fourier spectrum requiring all freq
arXiv:2608.27885v1 Announce Type: new Abstract: Multimodality translation (e.g., text-to-image) is a core generative AI task. However, existing approaches (1) follow generative paths that do not direc
This WikiSkill paper from Google is a must-read. At a high level, it shows the effectiveness of persistent agents, knowledge bases, and skills. @karpathy popularized LLM Wikis. But this paper provides
arXiv:2608.28138v1 Announce Type: new Abstract: Adapting video vision-language models (VLMs) is computationally expensive because video inputs produce a large number of visual tokens, making both fine
arXiv:2608.28018v1 Announce Type: new Abstract: Knowledge-intensive reasoning requires Large Language Models (LLMs) to ground answers in provided evidence. When evidence is insufficient, it is desirab
arXiv:2608.28195v1 Announce Type: new Abstract: Optical character recognition (OCR) for handwritten Indic manuscripts is essential for large-scale digitization and computational access to manuscript h
arXiv:2603.20111v2 Announce Type: replace Abstract: The Joint-Embedding Predictive Architecture (JEPA) is often seen as a non-generative alternative to likelihood-based self-supervised learning, empha
arXiv:2608.28549v1 Announce Type: new Abstract: Recent generative approaches to geometry estimation adapt pretrained image diffusion models and treat the task as image-conditioned generation. Leveragi
arXiv:2608.27562v1 Announce Type: new Abstract: Translating continuous, noisy egocentric video streams into discrete, temporally ordered action steps is fraught with visual challenges. Heavy ego-motio
arXiv:2608.28008v1 Announce Type: new Abstract: In this paper, we propose a new token compression paradigm for video Multimodal Large Language Models (MLLMs), termed Visual Token Coding (VTC). Inspire
arXiv:2608.27753v1 Announce Type: new Abstract: Despite the rapid advancement of Vision-Language Models (VLMs), their linguistic reach remains largely confined to high-resource languages, leaving the
arXiv:2608.27658v1 Announce Type: new Abstract: Subword tokenization hinders low-resource language processing by imposing frequency patterns from dominant languages onto script-sharing variants. Byte-
arXiv:2608.28240v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) delivers real-time and high-fidelity rendering but remains challenged by unconstrained in-the-wild scenes, where drastic ap
arXiv:2608.27481v1 Announce Type: new Abstract: Knowledge-intensive multi-hop question answering requires systems to select evidence and compose dependent facts, yet multilingual benchmarks usually tr
hi i make tool for this called llmog it's purpose to make llms free to - auto annotation datasets - reclassification existing yolo datasets running totally local using llama cpp or vllm or use externa
arXiv:2608.27239v1 Announce Type: cross Abstract: Adverse drug reactions (ADRs) are a major, largely preventable source of patient harm. In high-income settings, electronic health records store a pati
arXiv:2602.20159v3 Announce Type: replace-cross Abstract: Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grou
arXiv:2608.26581v1 Announce Type: new Abstract: Low-bit quantization offers a promising avenue for reducing the computational and memory demands of Multimodal Large Language Models (MLLMs). Recent har
arXiv:2608.26469v1 Announce Type: new Abstract: In many reinforcement learning (RL) domains, environments are connected by prerequisite relations, such as difficulty-increasing edits or parameter incr
arXiv:2608.27088v1 Announce Type: cross Abstract: While most phenotyping platforms rely primarily on image-based measurements, advanced plant characterization requires the integration of active physio
arXiv:2608.26141v1 Announce Type: new Abstract: Multimodal large language models have demonstrated strong document reasoning capabilities by incorporating explicit thinking processes. While this capab
arXiv:2608.26204v1 Announce Type: cross Abstract: Computer Use Agents (CUAs) are increasingly deployed to navigate mobile and desktop applications on behalf of users, yet no benchmark comprehensively
arXiv:2608.26193v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) achieve strong performance on VQA and scene understanding, yet affective reasoning remains vulnerable to shortc
arXiv:2608.26747v1 Announce Type: new Abstract: Scientific LLM agents have shown promise in literature reasoning, tool use, and experiment planning, but it remains unclear whether they can autonomousl
arXiv:2608.26780v1 Announce Type: new Abstract: Control system design is critical for modern industry, such as chemical process temperature regulation and aero-engine control. However,traditional cont
arXiv:2507.11515v2 Announce Type: replace-cross Abstract: Operating Large Language Models (LLMs) on edge devices is increasingly challenged by limited communication bandwidth and strained computationa
arXiv:2608.26993v1 Announce Type: new Abstract: Explicit visual intermediates can help multimodal large language models (MLLMs) externalize spatial evidence and updated visual states, but their utilit
arXiv:2608.26571v1 Announce Type: new Abstract: Contrastive reinforcement learning (CRL) scales effectively in goal-conditioned tasks by casting policy learning into a self-supervised contrastive obje
arXiv:2608.27095v1 Announce Type: new Abstract: Age-related macular degeneration (AMD) and diabetic macular edema (DME) are leading causes of vision loss, and optical coherence tomography (OCT) is the
arXiv:2608.26533v1 Announce Type: cross Abstract: Autonomous driving motion planners generate and select candidate trajectories while accounting for interactions with surrounding agents. However, thes
arXiv:2608.26592v1 Announce Type: new Abstract: Following clinical decision pathways (CDPs) defined by clinical practice guidelines is essential for safe and reliable medical decision-making. However,
arXiv:2608.26332v1 Announce Type: new Abstract: Managed LLM services are now part of real production systems, but model selection and service planning still rely heavily on capability benchmarks that
arXiv:2608.26689v1 Announce Type: new Abstract: While AI-assisted text-based counseling is gaining attention, it remains empirically unclear which counselor behaviors are associated with higher dialog
arXiv:2608.26888v1 Announce Type: new Abstract: Many recent underwater simulators emphasize visual realism at the expense of physical fidelity, focusing on shallow-water effects with limited relevance
arXiv:2608.26414v1 Announce Type: new Abstract: Medical guidelines encode rich, evidence-based decision logic, yet the specific decision artifact a clinician needs is hard to locate within a guideline
arXiv:2608.26868v1 Announce Type: new Abstract: Recent advances in SLAM have leveraged 3DGS for photorealistic reconstruction and novel view synthesis. However, most methods rely on RGB-D input, which
arXiv:2608.27406v1 Announce Type: cross Abstract: State-of-the-art action-conditioned video models are typically restricted to a single robot embodiment, preventing them from leveraging the vast corpu
arXiv:2608.26505v1 Announce Type: new Abstract: The Poppy Humanoid is an open-source, low-cost robot suitable for research and education in artificial intelligence. However, we are unaware of any publ
arXiv:2608.27214v1 Announce Type: new Abstract: Open World Object Detection (OWOD) built on multimodal foundation models often suffers from semantic ambiguity caused by unidirectional text-to-vision m
arXiv:2608.26656v1 Announce Type: cross Abstract: Multi-object removal in 3D scenes is challenging due to severe occlusions, semantic entanglement, and the difficulty of maintaining geometric and mult
arXiv:2608.27244v1 Announce Type: cross Abstract: An LLM call in a semantic data processing system is expensive enough to dominate query cost, yet slow enough to hide a CPU-side learner's update behin
arXiv:2608.27122v1 Announce Type: new Abstract: Directed graph learning naturally leads to trainable nonsymmetric propagation operators with distinct right and left spectral structures. Building on th
arXiv:2608.26932v1 Announce Type: new Abstract: Accurate state estimation for autonomous underwater vehicles performing close-range seafloor sampling remains challenging. In low-altitude operation, do
arXiv:2608.27455v1 Announce Type: new Abstract: Recent advances in inference-time scaling have significantly improved the reasoning performance of large language models (LLMs). However, these methods
arXiv:2608.26357v1 Announce Type: new Abstract: Large language models (LLMs) exhibit uneven multilingual performance, especially when dealing with low-resource languages. Inference-time intervention o