Knowledge catalogue
A benchmarking post testing 63 different samplers combined with the linear_quadratic noise scheduler for LTX-2.3 (Lightricks' audio-video generation model) . The linear_quadratic scheduler was origina
arXiv:2604.15645v1 Announce Type: new Abstract: We present PINNACLE, an open-source computational framework for physics-informed neural networks (PINNs) that integrates modern training strategies, mul
arXiv:2604.15670v1 Announce Type: new Abstract: Reasoning segmentation has recently expanded from ground-level scenes to remote-sensing imagery, yet UAV data poses distinct challenges, including obliq
🤯QWEN 3.6 35B-A3B IS INSANE AT CODING @unslothai recently dropped Qwen3.6-35B-A3B-GGUF The first open Qwen3.6 model and it’s solid. This MoE beast is cooking on benchmarks: 🧠SWE-bench Verified: 73.4 (
arXiv:2604.15736v1 Announce Type: cross Abstract: While Multimodal Large Language Models (MLLMs) excel at generic video understanding, their ability to support specialized, rule-grounded decision-maki
arXiv:2604.15828v1 Announce Type: new Abstract: Hyperspectral imaging enables fine-grained recognition of materials by capturing rich spectral signatures, but learning robust classifiers is challengin
arXiv:2604.16262v1 Announce Type: new Abstract: Recent advances in language models have substantially improved Natural Language Understanding (NLU). Although widely used benchmarks suggest that Large
arXiv:2604.13940v1 Announce Type: new Abstract: Scientific peer review faces mounting strain as submission volumes surge, making it increasingly difficult to sustain review quality, consistency, and t
arXiv:2604.14849v1 Announce Type: new Abstract: Purpose: Adaptive skip modules can improve medical image segmentation, but searching for them is computationally costly. Implantable Adaptive Cells (IAC
arXiv:2604.14884v1 Announce Type: new Abstract: Small object detection remains a significant challenge due to feature degradation from downsampling, mutual occlusion in dense clusters, and complex bac
arXiv:2604.14866v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated significant potential in medical image analysis, yet their application in intraoral photography remains
arXiv:2604.15093v1 Announce Type: cross Abstract: Mobile agents powered by vision-language models have demonstrated impressive capabilities in automating mobile tasks, with recent leading models achie
arXiv:2604.14513v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used in scientific peer review, assisting with drafting, rewriting, expansion, and refinement. However, ex
arXiv:2604.14725v1 Announce Type: cross Abstract: Recent advances in query optimization have shifted from traditional rule-based and cost-based techniques towards machine learning-driven approaches. A
This post announces Ornstein3.6-35B-A3B-GGU, a fine-tuned variant of Qwen 3.6 35B model available on Hugging Face, with the author claiming it represents a high-quality optimization of the base model.
This appears to be a tweet by Jeremy Howard, a prominent figure in AI and machine learning, likely discussing the need to increase certain metrics or performance benchmarks in AI development or a rela
arXiv:2604.13448v1 Announce Type: new Abstract: Human-object interaction (HOI) detection aims to detect interactions between humans and objects in images. While recent advances have improved performan
arXiv:2604.13717v1 Announce Type: new Abstract: LLM-as-a-judge, using a language model to score or rank candidate responses, is widely used as a scalable alternative to human evaluation in RLHF pipeli
As organizations transition from experimentation with AI to full-scale production, the demand for mission-critical security and absolute data availability has become the primary benchmark for enterpri
arXiv:2503.10522v4 Announce Type: replace-cross Abstract: Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a
arXiv:2604.13846v1 Announce Type: new Abstract: Personalized Large Language Models (LLMs) facilitate more natural, human-like interactions in human-centric applications. However, existing personalizat
arXiv:2604.13065v1 Announce Type: new Abstract: LLMs can execute every step of chain-of-thought reasoning correctly and still produce wrong final answers. We introduce the Novel Operator Test, a bench
arXiv:2604.13371v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly described as possessing strong reasoning capabilities, supported by high performance on mathematical, logi
arXiv:2510.02213v2 Announce Type: replace Abstract: Density map estimation enables accurate object counting in heavily occluded, and densely packed scenes where detection-based counting fails. In mult
arXiv:2604.13728v1 Announce Type: cross Abstract: We present a hybrid retrieval system for COVID-19 scientific literature, evaluated on the TREC-COVID benchmark (171,332 papers, 50 expert queries). Th
This r/StableDiffusion post is a community-driven benchmark comparing multiple quantization formats — fp8, nvfp4, fp16, and INT8 — of Baidu's ERNIE Image Turbo text-to-image model, using a standardize
arXiv:2604.13713v1 Announce Type: new Abstract: Metaphor detection models achieve strong benchmark performance, yet it remains unclear whether this reflects transferable generalization or lexical memo
New insane model from Jackrong on @huggingface 🤯 Qwen3.5-9B-GLM5.1-Distill-v1 🧠 Distilled on GLM-5.1 reasoning ⚙️ Deeper thinking than base model 🧪 Benchmarks coming soon ✅ Fits on 8GB VRAM ✍️ New mod
arXiv:2604.13791v1 Announce Type: new Abstract: Accurate lesion segmentation in ultrasound images is essential for preventive screening and clinical diagnosis, yet remains challenging due to low contr
arXiv:2604.13730v1 Announce Type: new Abstract: Continual learning enables models to acquire new knowledge over time while retaining previously learned capabilities. However, its application to text-t
There’s a fault line running through enterprise AI, and it’s not the one getting the most attention. The public conversation still tracks foundation models and benchmarks—GPT versus Gemini, reasoning
arXiv:2604.13928v1 Announce Type: new Abstract: Industrial time-series data from real production environments exhibits substantially higher complexity than commonly used benchmark datasets, primarily
arXiv:2512.14234v2 Announce Type: replace Abstract: Human communication is inherently multimodal and social: words, prosody, and body language jointly carry intent. Yet most prior systems model human
This r/StableDiffusion post presents a community benchmark testing how three compact, fast AI image generation models — ERNIE Turbo, Flux.2 Klein 4B, and Z-Image Turbo — handle complex and unconventio
If it can’t parse, it can’t perform. ❌ Reliable document understanding is fundamental to enterprise-grade #AgenticAutomation. We're excited to see the release of ParseBench, a new open-source benchmar
arXiv:2604.12470v1 Announce Type: new Abstract: Accurate vehicle counting through video surveillance is crucial for efficient traffic management. However, achieving high counting accuracy while ensuri
arXiv:2604.12995v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly integrated into real-world decision-making, including in the domain of public policy. Yet, their ability t
arXiv:2512.09664v2 Announce Type: replace-cross Abstract: We describe SynthPix, a synthetic image generator for Particle Image Velocimetry (PIV) with a focus on performance and parallelism on accelera
arXiv:2604.12116v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as tool-augmented agents capable of executing system-level operations. While existing benchmarks
arXiv:2604.12951v1 Announce Type: new Abstract: The most cited calibration result in deep learning -- post-temperature-scaling ECE of 0.012 on CIFAR-100 (Guo et al., 2017) -- is below the statistical
arXiv:2604.13029v1 Announce Type: cross Abstract: The effectiveness of Direct Preference Optimization (DPO) depends on preference data that reflect the quality differences that matter in multimodal ta
arXiv:2604.10335v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong performance in math reasoning benchmarks, but their performance varies inconsistently across problems wi
arXiv:2604.11491v1 Announce Type: cross Abstract: As generative models enable rapid creation of high-fidelity images, societal concerns about misinformation and authenticity have intensified. A promis
arXiv:2506.07523v3 Announce Type: replace Abstract: Large language models (LLMs) seem to offer an easy path to interpretability: just ask them to explain their answers. Yet the features driving an ans
arXiv:2604.05767v2 Announce Type: replace-cross Abstract: We present BADAS-2.0, the second generation of our collision anticipation system, building on BADAS-1.0, which showed that fine-tuning V-JEPA2
arXiv:2505.18931v4 Announce Type: replace Abstract: Understanding and inferring causal relationships from texts is a core aspect of human cognition and is essential for advancing large language models
arXiv:2604.11632v1 Announce Type: new Abstract: We introduce CARTBENCH, a museum-grounded benchmark for evaluating vision-language models (VLMs) on Chinese artworks beyond short-form recognition and Q
arXiv:2604.10825v1 Announce Type: new Abstract: We introduce CheeseBench, a benchmark that evaluates large language models (LLMs) on nine classical behavioral neuroscience paradigms (Morris water maze
arXiv:2604.09836v1 Announce Type: new Abstract: AI agents hold growing promise for accelerating scientific discovery; yet, a lack of frontier evaluations hinders adoption into real workflows. Expert-w
arXiv:2604.11581v1 Announce Type: new Abstract: LLM evaluations drive which models get deployed, which safety standards get adopted, and which research conclusions get published. Yet these scores carr
arXiv:2404.18905v3 Announce Type: replace-cross Abstract: Randomized trials are considered the gold standard for making informed decisions in medicine, yet they often lack generalizability to the pati
arXiv:2601.11428v4 Announce Type: replace Abstract: Neural PDE solvers have shown strong performance on standard benchmarks, but their robustness under deployment-relevant distribution shifts remains
arXiv:2507.03336v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly tasked with invoking enterprise APIs, yet they routinely falter when near-duplicate tools vie for the
arXiv:2604.11177v1 Announce Type: new Abstract: We benchmark how internal reasoning traces, which we call thought streams, affect video scene understanding in vision-language models. Using four config
arXiv:2604.11547v1 Announce Type: cross Abstract: While large language models hold promise for complex medical applications, their development is hindered by the scarcity of high-quality reasoning dat
arXiv:2509.04334v4 Announce Type: replace Abstract: Geographic reasoning is a fundamental cognitive capability that requires models to infer plausible locations by synthesizing visual evidence with sp
arXiv:2603.16849v2 Announce Type: replace Abstract: Adapting transformer positional encodings to graphs and meshes faces a fundamental tension: exact spectral methods require cubic-complexity eigendec
arXiv:2604.11072v1 Announce Type: new Abstract: Existing approaches to monitoring AI agents rely on supervised evaluation: human-written rules or LLM-based judges that check for known failure modes. H
arXiv:2601.22361v2 Announce Type: replace-cross Abstract: Assessing the veracity of online content has become increasingly critical. Large language models (LLMs) have recently enabled substantial prog
NEW: Added @OpenRouter's new free stealth model, Elephant-Alpha, to Hermes Agent, which you can now access if you run `hermes update`! I also had Hermes come up with an agentic benchmark on the fly to