Knowledge catalogue
arXiv:2607.25993v1 Announce Type: new Abstract: Ultra-high-resolution (UHR) remote-sensing (RS) imagery provides fine-grained Earth-observation evidence over city-scale scenes, but poses a fundamental
arXiv:2607.25432v1 Announce Type: new Abstract: Scribble annotations offer an efficient alternative to costly pixel-wise labeling for medical image segmentation, yet in real clinical scenarios, scribb
arXiv:2607.25451v1 Announce Type: new Abstract: Language models are almost always quantized before they are deployed, and a growing line of work asks whether quantization also lowers their privacy ris
I bought an RTX 5090 last year just to run 27B models natively. I even fine-tuned it with my own data using LoRA, building RAGs and was pretty damn happy with the results at first. But, Q8 quantizatio
BREAKING: Grok 4.5 (high) ranks #1 on the HighWalk benchmark, which tests how well AI agents update technical specifications from code changes. Grok delivered the best combination of quality and opera
BREAKING: Grok 4.5 just claimed the top spot on the new HighWalk Benchmark. The independent test measures how well AI models update real technical specifications from 46 Laravel commits — heavy on cod
BREAKING: Grok 4.5 ranked #1 on LaurenBench with a score of 56.9%, ahead of Claude Sonnet 5, GLM 5.2, Claude Opus 5, Kimi K3 and GPT-5.6. The benchmark tests real-world AI agents across conversation,
SpaceXAI has released its new Grok Voice Think Fast 2.0, which on the Artificial Analysis Speech‑to‑Speech benchmark outperformed leading models from OpenAI, Google, Alibaba and DeepSlate. The claim w
arXiv:2602.10430v2 Announce Type: replace-cross Abstract: Off-policy policy optimization reuses historical behavior, including negative-advantage samples that suppress known failures. We show that rep
arXiv:2607.25295v1 Announce Type: new Abstract: Tensorial multi-view clustering (TMC) has achieved strong performance due to its ability to capture high-order correlations across multiple views. Most
arXiv:2607.25271v1 Announce Type: cross Abstract: Classical compute-optimal scaling laws assume an unbounded supply of fresh pretraining data, yet pretraining is increasingly entering a regime in whic
arXiv:2509.07829v4 Announce Type: replace-cross Abstract: Literary translation has recently gained attention as a distinct and complex task in machine translation research, yet translation by small op
Hey everyone, I recently finished pre-training BetterGPT-150M, a small, lightweight causal language model with ~152 million parameters.Trained on 15B tokens. Dataset & Training: Trained across stable
arXiv:2607.24804v1 Announce Type: cross Abstract: Recommendation systems have undergone significant transformations in the past years. The transition from traditional feature interaction modules to ge
arXiv:2607.25244v1 Announce Type: new Abstract: Foundation models for 12-lead electrocardiograms (ECGs) transfer well across clinical tasks, but the physiological knowledge encoded in their representa
arXiv:2607.24996v1 Announce Type: cross Abstract: Neural networks are hindered by accumulating dormant neurons and loss of expressivity throughout training, particularly in non-stationary data setting
arXiv:2607.25929v1 Announce Type: cross Abstract: Deep generative models (DGMs) are widely used for complex high-dimensional data and increasingly applied to spatial and spatio-temporal modeling. Thei
arXiv:2607.25340v1 Announce Type: new Abstract: The same episode of atrial fibrillation is a minor finding in a healthy adult and grounds for anticoagulation in an elderly patient with hypertension: i
arXiv:2607.24763v1 Announce Type: new Abstract: Masked diffusion language models (MDLMs) are advancing rapidly, yet the evaluation standards needed to reliably interpret their progress have not kept p
arXiv:2607.24754v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to provide mental health support, requiring reliable evaluation of safety, empathy, and therapeutic
arXiv:2607.25308v1 Announce Type: cross Abstract: Training large language models (LLMs) to act in long-horizon games is a promising step toward generalist decision-making, yet reinforcement learning w
arXiv:2607.25239v1 Announce Type: new Abstract: Referring multi-object tracking (RMOT) extends tracking from category-driven perception to language-guided understanding by grounding object trajectorie
Disaggregated AI inference is proving to be more than a complementary answer to the prefill and decode bottleneck slowing enterprise AI at scale, and Cerebras and AMD just announced a partnership to b
arXiv:2607.16891v2 Announce Type: replace-cross Abstract: A truckload carrier must accept or reject each load tender within seconds. The decision depends on fleet state, hours-of-service (HOS) clocks,
arXiv:2607.11509v2 Announce Type: replace Abstract: Medical image anomaly detection remains challenging because networks pretrained on natural images often exhibit limited adaptability to medical imag
arXiv:2607.25070v1 Announce Type: cross Abstract: Radio Frequency Fingerprinting (RFFP) has emerged as a promising approach for device authentication by exploiting hardware-specific impairments embedd
arXiv:2607.26023v1 Announce Type: new Abstract: Graph foundation models (GFMs) have emerged as a promising paradigm for transferring knowledge across graph domains and tasks. Real-world graphs associa
arXiv:2607.25021v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can connect visualization patterns to external causes, consequences, and domain knowledge, but the evidential b
Sorry if flair is wrong. I decided to finally get a ChatGPT subscription after some conversations with it about health issues with my dog. I've only used AI for coding work, primarily Claude, but I fe
arXiv:2509.11285v2 Announce Type: replace-cross Abstract: Class-Incremental Learning (CIL) in deep neural networks is conventionally framed as an iterative gradient-based optimization problem, incurri
arXiv:2606.20233v2 Announce Type: replace Abstract: Cinematic compositing aims to integrate green-screen characters into novel environments while maintaining physical and photometric realism. Previous
arXiv:2607.25294v1 Announce Type: cross Abstract: Real-world tasks often require models to learn from task-specific context rather than relying only on pre-trained knowledge. While recent work has hig
arXiv:2409.12760v3 Announce Type: replace Abstract: To help address the occlusion problem in panoptic segmentation and image understanding, this paper proposes a new large-scale dataset named COCO-OLA
arXiv:2607.24999v1 Announce Type: cross Abstract: LLM cognitive scores are increasingly summarized as per-ability profiles whose dimensions should converge across tasks, respond selectively to matched
arXiv:2607.25045v1 Announce Type: new Abstract: Electroencephalography (EEG) analysis in cognitive studies requires specialized expertise and involves many defensible choices over contrasts, channels,
arXiv:2607.25681v1 Announce Type: new Abstract: Cognitive distortion amplifies negative emotions and contributes to mental health disorders. Cognitive Behavioral Therapy (CBT) is an effective way to a
ComfyUI Face Swap Tutorial: Fast, Clean Results VFX artist @heydoughogan walks through a fully automated face swap workflow built inside ComfyUI - combining Florence 2, SAM2, and WAN Video into a sing
arXiv:2509.16780v3 Announce Type: replace-cross Abstract: Large language models (LLMs) show promise as educational aids but often lack alignment with specific course materials. We investigate Retrieva
arXiv:2501.17296v4 Announce Type: replace-cross Abstract: Multiphysics simulations play an essential role in accurately modeling complex interactions across diverse scientific and engineering domains
arXiv:2607.25605v1 Announce Type: new Abstract: This paper presents a set-theoretic formalization of the classical usuli method of al-Sabr wa al-Taqsim (Examination and Division) for extracting legal
arXiv:2607.25169v1 Announce Type: cross Abstract: Message-passing graph neural networks are bounded by the 1-WL test and can miss topological structure that distinguishes non-isomorphic graphs. Positi
The Together AI platform’s dedicated inference architecture consists of three immutable entities: **configs** (engine, GPU type/count, parallelism and optimization profile), **deployments** (a specifi
arXiv:2607.25018v1 Announce Type: new Abstract: Large language model (LLM) cascades reduce inference cost by routing easy queries to a small model and deferring hard queries to a larger one. Productio
arXiv:2607.18946v2 Announce Type: replace Abstract: In this work, we address diacritic restoration for Arabic speech transcripts. Most speech data are undiacritized, limiting the ability of modeling f
arXiv:2607.25633v1 Announce Type: cross Abstract: Large language models (LLMs) are costly intellectual assets that remain exposed to unauthorized redistribution and commercial misuse. Injected fingerp
arXiv:2607.25408v1 Announce Type: new Abstract: A growing body of 2026 work applies control theory to LLM agents: Lyapunov-certified stability for tool-mediated controllers (Prinos et al., 'Stable Age
arXiv:2607.25664v1 Announce Type: new Abstract: Machine learning demand forecasts optimize statistical accuracy yet leave excess operational volatility that inflates safety stock and amplifies the Bul
arXiv:2607.25283v1 Announce Type: new Abstract: This paper presents ContractHIL-HLS, a contract-aligned multi-agent workflow for practical high-level synthesis (HLS) engineering. The workflow makes th
arXiv:2607.25609v1 Announce Type: cross Abstract: Understanding disease trajectories from longitudinal clinical data remains challenging due to complex temporal dynamics and heterogeneous patient coho
arXiv:2510.07884v3 Announce Type: replace-cross Abstract: Weak-to-strong generalization provides a promising paradigm for scaling large language models (LLMs) by training stronger models on samples fr
arXiv:2601.03595v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) exhibit human-like cognitive reasoning strategies (eg backtracking, cross-verification) during the reasoning process,
arXiv:2607.25754v1 Announce Type: new Abstract: Cooperative navigation of multi-agent UAVs in complex environments faces key challenges including local optima traps, sparse rewards, learning imbalance
arXiv:2607.25569v1 Announce Type: cross Abstract: Recent advances in 3D Gaussian Splatting (3DGS)-based wireless radiance field (WRF) reconstruction provide an efficient solution for wireless channel
arXiv:2607.25659v1 Announce Type: new Abstract: Rubric-based reinforcement learning enriches language model training by evaluating model outputs against explicit criteria. Yet in GRPO-style pipelines,
arXiv:2607.25291v1 Announce Type: new Abstract: The quadratic cost of self-attention makes long-context inference prohibitively expensive, and proxy-based block-sparse attention has become a practical
arXiv:2607.25487v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models translate natural-language commands into robot action sequences, but leading systems on the LIBERO-Plus robustness b
arXiv:2607.25400v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly entrusted with natural-language workflow instructions (e.g., retail-payment policies) that specify no
arXiv:2505.08060v3 Announce Type: replace Abstract: Modern coverage path planning (CPP) for holonomic UAVs in emergency response must contend with diverse environments where regions of interest (ROIs)
arXiv:2607.25370v1 Announce Type: cross Abstract: We develop a novel forecasting scheme to anticipate controller induced loss of control (LOC) in quadrotors and evaluate it on real LOC flight data fro
arXiv:2607.24766v1 Announce Type: new Abstract: Large language models (LLMs) can generate individual charts, but coordinated multi-view visualizations (CMVs), where views share data flows and cross-vi