Knowledge catalogue
arXiv:2608.00066v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact heart-rate estimation from facial videos, but its weak physiological signal is easily corrupted b
arXiv:2607.18361v2 Announce Type: replace Abstract: Deep neural networks have become a promising approach for IMU-based sensing, but their scalability is fundamentally limited by costly labeled data a
Picking the right agent harness is now a crucial skill for any AI engineer. Imagine using the same model, same task, and same prompt. Now move it between two agent harnesses and the cost per success c
arXiv:2608.01598v1 Announce Type: new Abstract: Simulating human-like Theory of Mind (ToM) has been a longstanding problem in natural language processing (NLP). To address this, existing works introdu
PipeNetwork/minimax-h3-mlx MiniMax released MiniMax-H3 two days ago - they describe it as a 'a general-purpose, omni-modal generative system', which in practice means it accepts text, images, audio an
arXiv:2608.01760v1 Announce Type: new Abstract: Adverse weather image restoration aims to recover clear visibility from degraded images in complex weather conditions. Existing works attempt to address
arXiv:2608.00646v1 Announce Type: new Abstract: Screen content images are generally composed of texts and graphics. Compared to natural images, these man-made images contain a large quantity of sharp
arXiv:2608.01354v1 Announce Type: new Abstract: Recent studies develop pixel-level multimodal large language models (MLLMs) that support both Region Segmentation and Region Understanding, extending mu
arXiv:2608.01158v1 Announce Type: new Abstract: We introduce PlainMedScale, a topic-aligned medical corpus spanning four levels of comprehensibility in German and English, drawn from MSD (professional
arXiv:2608.01072v1 Announce Type: new Abstract: Autoregressive rigging models such as UniRig and SkinTokens perform well on articulated characters, but their ability to generalize to plant structures
arXiv:2608.01475v1 Announce Type: new Abstract: Neural networks that can grow or both grow and shrink during learning, referred to as growing neural networks and elastic neural networks, respectively,
arXiv:2608.01910v1 Announce Type: new Abstract: In real-world hyperspectral scenes, pixel representations are often ambiguous due to factors such as spectral similarity, mixed pixels, and local contex
arXiv:2608.01133v1 Announce Type: new Abstract: Evaluating Multi-Agent Reinforcement Learning (MARL) policies in autonomous driving fundamentally relies on extrinsic statistical indicators (e.g., rewa
arXiv:2409.15600v3 Announce Type: replace Abstract: A representation of a molecule or material should be invariant to the symmetries of physics, unique, continuous, efficient and general. These proper
arXiv:2608.01431v1 Announce Type: cross Abstract: Polymer property prediction and inverse generative design targeting desired properties are two crucial tasks in machine learning-assisted polymer desi
arXiv:2608.00440v1 Announce Type: new Abstract: Recent image generators can synthesize convincing human-centric images, yet producing a useful collection remains different from producing a single succ
arXiv:2608.00489v1 Announce Type: new Abstract: Single-photon avalanche diode (SPAD) cameras are promising for low-light and high-dynamic-range intensity imaging, but their practical use is limited by
arXiv:2608.00902v1 Announce Type: new Abstract: LLM agents accumulate long trajectories of reasoning steps, tool calls, and environment feedback, making the KV cache a major inference bottleneck. KV c
arXiv:2608.02372v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in task-oriented dialogue systems that support multi-step decision-making in high-stakes domains
arXiv:2608.00045v1 Announce Type: new Abstract: This study shows that textual descriptors alone can predict early-stage startup success, defined as Exit, without relying on contextual, financial, or h
arXiv:2608.01819v1 Announce Type: new Abstract: To improve the operational readiness of combat aircraft engines and reduce unplanned maintenance costs, accurately estimating the remaining useful life
arXiv:2608.00383v1 Announce Type: cross Abstract: Logical rule induction seeks interpretable rules that transfer across propositional schemas. This requires respecting symmetries: atom naming, example
arXiv:2608.02084v1 Announce Type: cross Abstract: Binary function embedding models are trained to encode the semantics of binary code in such a way that they can be generalized to a variety of reverse
arXiv:2608.01201v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E AD) systems integrate perception, prediction, and planning into a single differentiable architecture. While these m
arXiv:2608.02480v1 Announce Type: cross Abstract: With AI systems gaining more access to individuals' information, it is important to protect privacy when reporting statistical answers. Equally import
arXiv:2608.01864v1 Announce Type: cross Abstract: Predicting drought risk is essential for anticipating impacts on water resources, agriculture, ecosystems, and climate adaptation planning. Yet drough
arXiv:2608.02545v1 Announce Type: new Abstract: Reachability analysis for visuomotor policies is difficult because large visual encoders make end-to-end set propagation computationally expensive and e
Found this quant, so thought I would share, since its the best I've found so far for running on my mac (m3 ultra). It's got dspark/mtp support so runs faster than anything else I've tried. The tok/s o
arXiv:2608.01495v1 Announce Type: new Abstract: Detection transformer models, including DETR and its extensions, learn to output a set of object-level embeddings that can be simultaneously decoded int
arXiv:2608.01678v1 Announce Type: cross Abstract: Existing skill generation methods largely rely on heuristics or pipeline-style consolidation, which must be specially designed for different evidence
arXiv:2608.00129v1 Announce Type: new Abstract: Knowledge distillation (KD) is a widely utilized technique for transferring knowledge from a large model (the teacher) to a smaller model (the student).
arXiv:2608.01348v1 Announce Type: new Abstract: Data augmentation, which simulates diverse visual variations to expand the source distribution and induce synthetic domain shifts, is a simple yet effec
arXiv:2608.01347v1 Announce Type: new Abstract: Large reasoning models used as coding agents incur costs from deliberation, tool calls, and repeated agent turns, yet the causal effect of prompt wordin
arXiv:2608.02129v1 Announce Type: new Abstract: In-context learning (ICL) has attracted increasing attention for enabling models to perform new tasks using only a few ``input--output'' prompt examples
arXiv:2608.00687v1 Announce Type: new Abstract: LiDAR point clouds provide explicit, deterministic physical boundaries critical for collaborative safety-critical perception. However, wireless channels
arXiv:2608.01690v1 Announce Type: new Abstract: Biological wet-lab protocols are written for trained researchers and often leave routine operations, state-dependent conditions, and contextual paramete
arXiv:2608.02053v1 Announce Type: cross Abstract: Brain tissue microstructure estimation with machine learning provides higher computational efficiency than conventional fitting. However, machine lear
arXiv:2602.21429v3 Announce Type: replace Abstract: Flow-based generative models, such as diffusion models and flow matching models, have achieved remarkable success in learning complex data distribut
arXiv:2608.01978v1 Announce Type: new Abstract: Audio-driven portrait animation has advanced rapidly with diffusion-based generative models, yet real-time one-shot generation with expressive emotion c
arXiv:2608.00837v1 Announce Type: new Abstract: Byte Pair Encoding (BPE) is widely used for subword tokenization, but standard BPE exposes every learned merge token to the downstream model, including
arXiv:2608.02575v1 Announce Type: new Abstract: Diffusion models rely on stochastic inputs, yet on finite-precision hardware, the 'randomness' they consume is realized as deterministic numerical orbit
arXiv:2608.00730v1 Announce Type: new Abstract: Viscous stains, characterized by high viscosity and complex rheological properties, remain a major challenge for robotic surface cleaning. Conventional
arXiv:2510.25693v3 Announce Type: replace-cross Abstract: State-space models (SSMs) are a widely used tool in time series analysis. In the complex systems that arise from real-world data, it is common
arXiv:2608.01422v1 Announce Type: new Abstract: Machine unlearning seeks to remove targeted information from trained models without requiring costly retraining. Existing optimization-based methods oft
arXiv:2506.07121v2 Announce Type: replace Abstract: Ensuring the safety and robustness of large language models (LLMs) is a fundamental challenge and a critical prerequisite for the responsible deploy
arXiv:2510.14546v2 Announce Type: replace Abstract: Embeddings from Visual-Language Models are increasingly utilized to represent semantics in robotic maps, offering an open-vocabulary scene understan
arXiv:2608.02144v1 Announce Type: new Abstract: Division-of-focal-plane (DoFP) color polarization cameras enable snapshot acquisition of color polarization mosaic images, but the inherently sparse sam
arXiv:2608.01186v1 Announce Type: new Abstract: While feed-forward 3D Gaussian Splatting (3DGS) enables efficient 3D reconstruction, achieving high-fidelity rendering remains challenging. Existing pix
arXiv:2608.01522v1 Announce Type: cross Abstract: Teaching a language model a skill it has not mastered is obstructed by three recurring difficulties: training data is scarce, ground-truth reasoning t
arXiv:2508.08645v3 Announce Type: replace Abstract: As multimodal large language models advance rapidly, the automation of mobile tasks has become increasingly feasible through the use of mobile-use a
Gas Town was intended to be reusable, but I only ever wound up using it to build itself. Gas Town fell apart at the seams with Opus 4.7. Up through 4.6 it was working brilliantly. With 4.7 we saw the
Qwen 3.8-Max, the latest model from @Alibaba_Qwen, is now available in Hermes Agent at 20% off. > hermes update 📢Meet Qwen3.8-Max — our most capable model to date. Next week, the open weights of Qwen3
arXiv:2608.02352v1 Announce Type: cross Abstract: Native computer use offers a general interface for agents to operate almost any software available to people, but requires long-horizon state tracking
Qwen-Image-3.0-Pro has made a massive leap from the previous generation, now ranking #5 globally. Appreciate the recognition! We will keep building.🚀 More exciting news from @Alibaba_Qwen: Qwen-Image-
Qwen3.8-Max, better and cheaper. Try it out. 👀 We ran a test between the new Qwen3.8-Max, Opus 5 and GPT-5.6 Sol. 3 models. same prompt. one-shot with the /design command. Reviewed gameplay features,
Qwen 3.8‑Max, Alibaba.Qwen’s latest large‑language model, has been added to Hermes Agent and can currently be accessed at a 20 % discount. The update aims to streamline integration of the model for de
arXiv:2608.01626v1 Announce Type: new Abstract: Short-term precipitation nowcasting is important for hydrometeorological early warning, especially when intense convective rainfall may trigger urban fl
arXiv:2608.01855v1 Announce Type: new Abstract: Fast dynamic obstacle avoidance (DOA) on uncrewed aerial vehicles (UAVs) demands not only low-latency control and actuation but also reliable perception
arXiv:2608.01810v1 Announce Type: new Abstract: Rubric-based LLM-as-judge pipelines often assume that evaluation criteria provide independent signals. In practice, however, criteria can be behaviorall
arXiv:2608.00147v1 Announce Type: new Abstract: Vision-language pretraining learns rich medical image representations from radiology reports, but previous model variants commonly operate within a sing