Knowledge catalogue
Thanks again for your interest in our work! Links here so they don’t get buried under “show more”: Paper 📄: https://arxiv.org/abs/2606.02373 Code 💻: https://github.com/pat-jj/harness-1 Model 🤗: https:
arXiv:2606.06814v1 Announce Type: cross Abstract: The transformer's emergent ability to perform in-context learning (ICL) has sparked a wide range of studies designed to understand its underlying mech
arXiv:2412.09119v3 Announce Type: replace Abstract: Machine unlearning, the process of selectively removing data from trained models, is increasingly crucial for addressing privacy concerns and knowle
arXiv:2606.06835v1 Announce Type: new Abstract: The performance gap across languages in LLMs is well documented, and closing it natively requires pretraining or fine-tuning on corpora that, for most l
arXiv:2606.06938v1 Announce Type: new Abstract: Vision-language models such as CLIP have achieved remarkable zero-shot recognition capabilities, yet their robustness against adversarial perturbations
arXiv:2606.07473v1 Announce Type: cross Abstract: Whisper, a widely adopted ASR model, is known to suffer from hallucinations - coherent transcriptions generated for non-speech audio entirely disconne
arXiv:2606.06893v1 Announce Type: new Abstract: Large language model agents increasingly rely on Skills to encode procedural knowledge, yet high-quality Skills remain costly to hand-write. This paper
blast from the past 3.5 years ago; some things have changed (esp. coding and math, via neurosymbolic techniques) but many haven’t: Bottom line: From the outset Large Language Models like GPT-3 have gr
ComfyUI, a node-based UI framework for Stable Diffusion and other AI models, continues active development and feature releases. The post celebrates ongoing progress and improvements to the platform, l
ChatGPT Plus users can generate approximately 50 images per rolling 3-hour window , with a daily maximum of around 200 images . Recent product updates have introduced new image models and occasional t
Automated lint: 47 errors, 12 warnings, 3 info
arXiv:2606.05357v1 Announce Type: new Abstract: Purpose: To develop an interpretable and trustworthy AI framework that combines deep learning based MRI Osteoarthritis Knee Score (MOAKS) prediction wit
arXiv:2606.05818v1 Announce Type: cross Abstract: Between April 1 and May 15, 2026, a group of 49 mathematicians compiled a dataset of research-level mathematics questions with known answers. Most of
arXiv:2403.00965v2 Announce Type: replace-cross Abstract: Only a small fraction of patients with chronic kidney disease (CKD) progress to dialysis, creating severe class imbalance that limits the perf
arXiv:2606.06345v1 Announce Type: new Abstract: Brain decoding is limited by the availability of labeled neural data, and remains challenging in low-data regimes. To address this issue, we investigate
arXiv:2606.05551v1 Announce Type: cross Abstract: Reliable decision making pipelines powered by machine learning models require uncertainty quantification (UQ) methods that come with explicit safety g
arXiv:2606.05232v1 Announce Type: cross Abstract: Efficient multimodal foundation models often rely on manually designed token-reduction operators, such as pruning, merging, pooling, and adaptive rewe
arXiv:2512.20627v2 Announce Type: replace-cross Abstract: Intent-Based Networking (IBN) offers a promising paradigm for intelligent and automated network control in Industrial Internet of Things (IIoT
arXiv:2511.21667v4 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) to reason often relies on Reinforcement Learning (RL) with task-specific verifiers. However, many real-w
arXiv:2602.07739v2 Announce Type: replace-cross Abstract: Embedding geometry plays a fundamental role in retrieval quality, yet dense retrievers for retrieval-augmented generation (RAG) remain largely
The Mac mini M4 uses unified memory architecture where CPU and GPU share a single 24GB memory pool, while the RTX 5060 has dedicated VRAM. Mac mini M4 is preferred for large model inference (70B param
arXiv:2606.05206v1 Announce Type: cross Abstract: Fragmentation is common in interdisciplinary fields with diverse methods and theoretical commitments. Predictive coding neuroscience is a clear exampl
arXiv:2606.05697v1 Announce Type: new Abstract: User interface (UI) and user experience (UX) evaluation is central to product development, yet reliable feedback still relies on recruiting human partic
arXiv:2606.06479v1 Announce Type: cross Abstract: Training recurrent neural networks (RNNs) requires assigning credit across long sequences of computations. Standard backpropagation through time (BPTT
arXiv:2606.05875v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves large language model (LLM) answer quality by grounding generation in external evidence, but processing ret
arXiv:2602.19327v3 Announce Type: replace-cross Abstract: A significant portion of recent research on Large Language Model (LLM) alignment focuses on developing new policy optimization methods based o
arXiv:2606.06102v1 Announce Type: new Abstract: Ultra-short-term solar irradiance prediction is critical for photovoltaic system dispatch and power grid stability. Existing approaches suffer from thre
arXiv:2512.15783v3 Announce Type: replace Abstract: This paper proposes a measurement standardisation framework that compresses expert-AI interactions into structured, comparable fields for prospectiv
Whether SpaceX/ Xai is making money on the deals with Google and Anthropic or losing money, they are waving the towel on winning the frontier model race— by arming their competitors rather than themse
3 weeks left til @aidotengineer world's fair! if you want to get on this year's map of top ai engineering companies, theres a few spots left we are sold out of: - presenting sponsors - model lab spons
arXiv:2606.06420v1 Announce Type: new Abstract: We present the first Komi-Yazva--Russian parallel corpus together with an explicit evaluation protocol for studying LLM translation in an endangered, ex
arXiv:2606.05687v1 Announce Type: new Abstract: In humanoid motion control, model predictive control (MPC) offers physically grounded prediction and constraint handling, while reinforcement learning (
No sooner did Anthropic file for its initial public offering of stock this week than it then put out a missive suggesting that AI model makers need to slow down to let us catch our breath — or else AI
The post appears to reference designer Vincent conducting frontier capability tests, likely related to AI model evaluation or benchmarking. The tone suggests this is commentary on ongoing AI developme
This article from Apify's blog covers the process of training AI chatbots, likely including techniques for data preparation, model selection, and fine-tuning approaches. The content is shared by Pinec
b9521 is an intermediate build release of llama.cpp, an open-source C/C++ library for large language model inference. The release is part of the continuous development cycle following other recent bui
B9530 is a release version of llama.cpp, a tool for LLM inference in C/C++ . It allows users to run large language models on everyday consumer hardware without expensive GPUs or cloud infrastructure .
arXiv:2606.05778v1 Announce Type: new Abstract: Traditional Image Aesthetic Assessment (IAA) methods mainly rely on regressing absolute Mean Opinion Scores (MOS). However, such a paradigm overlooks th
arXiv:2606.05711v1 Announce Type: new Abstract: Multi-agent systems built on large language models (LLMs) have become a prevailing paradigm for tackling complex reasoning, planning, and tool-use tasks
arXiv:2601.12983v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are increasingly used to automate chart generation from data tables, improving analysis and reporting effic
arXiv:2606.05523v1 Announce Type: new Abstract: Despite advances in safety alignment, prompt-rewriting attacks such as persona modulation, fictional framing and persuasion-based reformulation, can byp
Come visit our CVPR booth for hands-on experiences: – Neural video generation + sim drive – Selfies with @Tesla_Optimus – Real FSD test drives in Tesla models of your choice Chat directly with the tea
arXiv:2606.05645v1 Announce Type: new Abstract: Autonomous driving requires reasoning about how ego actions shape the evolution of the surrounding world. However, most end-to-end methods rely on direc
arXiv:2606.05185v1 Announce Type: cross Abstract: Mass gathering events are associated with critical safety incidents caused by insufficient crowd monitoring and inadequate emergency response coordina
arXiv:2606.05536v1 Announce Type: new Abstract: Out-of-distribution detection (OOD) is an indispensable technique when applying machine learning models to real-world scenarios. Most existing OOD detec
arXiv:2606.05816v1 Announce Type: new Abstract: T2I models cannot effectively capture sentiment from various types of text, including diaries, as they primarily focus on visual object-related patterns
arXiv:2606.05513v1 Announce Type: cross Abstract: Epidemic LLM forecasters are usually trained and evaluated as static supervised models, whereas operational pandemic forecasting is a streaming proces
arXiv:2606.05760v1 Announce Type: new Abstract: Deepfake videos are increasingly challenging the credibility of online content. Many existing detection methodology relies on complex, resource-intensiv
arXiv:2606.06461v1 Announce Type: new Abstract: Leveraging prior knowledge from pretrained policies, foundation models, or human operators offers an efficient alternative to learning robot skills from
arXiv:2606.05404v1 Announce Type: cross Abstract: Time series are often embedded in rich contexts that are essential for holistic modeling. Moreover, real-world practitioners often require end-to-end
arXiv:2606.06390v1 Announce Type: new Abstract: Indoor scene generation is crucial for robot simulation and modern interior design. However, complex layouts together with scarce 3D scene data make lea
arXiv:2606.06100v1 Announce Type: new Abstract: Vision-Language Models (VLMs) struggle with compositional reasoning that requires understanding inter-object relationships. A natural remedy is to injec
arXiv:2606.05769v1 Announce Type: new Abstract: Video event prediction (VEP) requires models to infer unobserved future states from partial video evidence. Existing video MLLMs usually verbalize inter
arXiv:2606.06458v1 Announce Type: cross Abstract: Multiple Instance Learning (MIL) addresses problems where supervision is available at the level of bags of instances and has been successfully applied
arXiv:2503.23300v2 Announce Type: replace Abstract: Understanding and predicting human visuomotor coordination is crucial for applications in robotics, human-computer interaction, and assistive techno
arXiv:2606.05917v1 Announce Type: cross Abstract: Long-video question answering remains challenging for Vision-Language Models (VLMs), as answer-relevant evidence is often sparse, transient, and tempo
arXiv:2606.06473v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery and machine learning engineering (MLE),
arXiv:2606.05785v1 Announce Type: new Abstract: Real-Time License Plate Detection and Recognition (LPDR) forms the backbone of modern smart cities. Although the YOLOV5-PDLPR model substantially improv
arXiv:2606.05261v1 Announce Type: new Abstract: Variable fonts enable continuous variation of glyph geometry along semantic design axes such as weight, width, slant, and optical size. However, constru
arXiv:2606.06080v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards is widely used for post-training reasoning models, but sparse outcome rewards make exploration difficul