Knowledge catalogue
arXiv:2608.21369v1 Announce Type: cross Abstract: Nigerian Pidgin is one of Africa's most widely spoken languages, yet remains severely underrepresented in language model evaluation. Existing benchmar
We officially surpassed 1M model downloads on @huggingface 🔥 Your 5 most downloaded models: 1. Qwen3.8 27B — 261K 2. Ling 3.0 flash — 158K 3. Ornith 1.5 35B A3B — 50K 4. Qwen3.5 4B DFlash — 49K 5. Gem
We plan to begin deploying Jalapeño in OpenAI’s compute infrastructure by year-end. It’s the first step in a multigenerational roadmap: Gen 2 is deep in development, and Gen 3 is taking shape. Each ge
arXiv:2608.22584v1 Announce Type: new Abstract: Two-stage neuro-symbolic architectures provide an elegant paradigm for visual problem solving by cleanly separating connectionist perception of predefin
arXiv:2608.22110v1 Announce Type: new Abstract: We ask what gets a language model onto the Apple Neural Engine (ANE) and what makes it fast there, and we answer with three measurements. We sweep a 64-
arXiv:2608.22614v1 Announce Type: new Abstract: Interpretability research increasingly asks when concepts emerge during training and whether linear probes recover real structure, but in language model
What do I want in AI? Here are just a few things. I want voice-enabled everything. I want things to be more proactive. I want to manage AI’s escalations (versus delegation). I want those escalations t
arXiv:2608.22985v1 Announce Type: new Abstract: Activation steering is often evaluated under the answer encoding used to construct the direction. A reported gain may reflect the intended judgment or c
arXiv:2608.21761v1 Announce Type: new Abstract: Large collections of street-view imagery provide rich visual information about urban environments, but extracting fine-grained geographic information fr
arXiv:2009.09083v4 Announce Type: replace-cross Abstract: The term intelligent system has emerged in the field of information technology as a category of computer systems derived from successful appli
arXiv:2608.23218v1 Announce Type: new Abstract: Advances in neural theorem provers have been impressive, but the successes obscure a broader vision of what AI can do for mathematics and how mathematic
arXiv:2608.22507v1 Announce Type: new Abstract: Long jumpers with below the knee amputation (BKA) that take off from their running-specific prosthesis (RSP) improved performances significantly over th
arXiv:2608.23295v1 Announce Type: new Abstract: Memory-based anomaly detectors store nominal training patches and score test patches against this memory. A patch selected for coverage therefore become
arXiv:2604.05779v2 Announce Type: replace-cross Abstract: While large language models (LLMs) demonstrate strong capabilities across diverse user queries, they still suffer from hallucinations, often a
arXiv:2608.21523v1 Announce Type: cross Abstract: One aim of neural network field theory is to put a quantum or effective field theory on a computer, with the network ensemble itself as the theory. We
arXiv:2608.22960v1 Announce Type: new Abstract: Coding agents are increasingly evaluated not only by whether they solve a task, but also by how they execute it. However, existing process-level evaluat
arXiv:2608.22948v1 Announce Type: cross Abstract: Large language models are increasingly used to propose research ideas, yet the prevailing ways of judging such ideas supply no shared decision rule: f
arXiv:2608.23299v1 Announce Type: new Abstract: Memory-based anomaly detectors store nominal training patches and score test patches against this memory. A patch selected for coverage therefore become
arXiv:2608.23474v1 Announce Type: cross Abstract: Vision-language models (VLMs) achieve strong performance on video and image-sequence benchmarks, yet it remains unclear whether they capture temporal
arXiv:2608.23075v1 Announce Type: cross Abstract: Learned surrogates for expensive inner solver blocks are a widely pursued route to faster multiphysics simulation. We report a controlled, end-to-end
arXiv:2608.22366v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly being used for document understanding, yet their role in Arabic and Islamic manuscript recognition remain
arXiv:2608.22504v1 Announce Type: new Abstract: Existing AI-for-PDE benchmarks primarily assess models in terms of predictive or approximation accuracy. In physics research, however, AI outputs often
arXiv:2608.22174v1 Announce Type: new Abstract: Unified multimodal models (UMMs) can perform both understanding and generation, raising a central question: can visual generation improve understanding?
arXiv:2608.23161v1 Announce Type: new Abstract: Heavy-duty vehicle diagnostics generate three disconnected data modalities: unstructured multi- lingual service complaints, high-dimensional sensor tele
arXiv:2608.22082v1 Announce Type: new Abstract: Patch-memory anomaly detectors assume that their reference bank is normal, an assumption that is difficult to guarantee when additional industrial image
arXiv:2608.23507v1 Announce Type: cross Abstract: Historical people may appear under different languages, scripts, and transcription traditions, while distinct individuals may share highly similar or
arXiv:2608.22339v1 Announce Type: new Abstract: Extracting skills from past successes is critical for the efficient evolution of Large Language Model (LLM) agents. Prevailing agent self-evolution para
arXiv:2608.22438v1 Announce Type: new Abstract: Persona-conditioned large language models (LLMs) are increasingly used to simulate survey responses across diverse domains. However, apparent response v
arXiv:2608.22233v1 Announce Type: cross Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shift by adapting a source model using unlabeled test data. Although me
arXiv:2608.23024v1 Announce Type: new Abstract: Counterfactual medical image generation aims to modify an existing image to reflect a hypothetical scenario in which certain characteristics of the imag
arXiv:2608.22347v1 Announce Type: new Abstract: A cognitive architecture is more than the module that reasons: it must also decide how long to think and what deserves the effort. We built a minimal bu
arXiv:2608.22421v1 Announce Type: new Abstract: World models predict action-conditioned futures and serve as critical internal simulators for downstream planning and control. However, catastrophic pre
arXiv:2602.13106v2 Announce Type: replace-cross Abstract: In recent years, there has been growing interest in understanding neural architectures' ability to learn to execute discrete algorithms, a lin
arXiv:2608.23221v1 Announce Type: cross Abstract: Historical retrieval for time-series prediction commonly treats past similarity as a proxy for usefulness. We ask a different question: which historic
arXiv:2608.22230v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for hate speech moderation, often within human--AI workflows in which reviewers provide feedback befo
arXiv:2608.22490v1 Announce Type: new Abstract: Safety alignment helps models adhere to human values, but it often reduces response utility. We ask a critical but understudied question: Does safety al
arXiv:2608.22127v1 Announce Type: new Abstract: Text-Attributed Graphs (TAGs) integrate graph structures and node-associated textual attributes, and recent studies have increasingly leveraged Large La
arXiv:2508.09846v2 Announce Type: replace Abstract: This paper presents an object-aware whole-body bilateral teleoperation framework for wheeled humanoid loco-manipulation. This framework combines who
In this installment of Rise of the AI Engineer, Stuart Sy from OpenAI, explains why the bottleneck has moved off the model and onto context, evals, and observability. The post Why better models don’t
arXiv:2608.22155v1 Announce Type: cross Abstract: The study of adversarial examples and their origins remains an open area of research. Mechanistic interpretability, and superposition in particular, o
arXiv:2608.21620v1 Announce Type: new Abstract: This paper investigates wearable-based recognition of human activities and gestures to support Human-Robot Interaction (HRI) in object-handover and asse
arXiv:2608.21662v1 Announce Type: cross Abstract: The topic of explanation in recommender systems has seen steady research attention since the earliest days of the field. With some exceptions, this wo
arXiv:2608.21752v1 Announce Type: new Abstract: It has long been known that well-trained neural networks can be compressed very strongly without affecting their performance, an important phenomenon th
arXiv:2608.22959v1 Announce Type: cross Abstract: While the top model on OmniDocBench now reaches 96.34% overall on printed-document parsing, the ability of current models to handle challenging handwr
arXiv:2608.22704v1 Announce Type: new Abstract: Long-form audio inputs make the KV cache the dominant memory cost of speech LLMs. Prefill-only KV compression methods permanently discard audio KV posit
arXiv:2608.21439v1 Announce Type: new Abstract: Game world models have recently demonstrated promising capabilities in generating visually coherent and action-controllable gameplay videos. However, no
arXiv:2608.22591v1 Announce Type: new Abstract: Robot policies receive heterogeneous observations at each decision step, yet sequence models differ in how they organize these inputs over time. We intr
WSJ: 'Anthropic more than doubled its revenue to 11.6 billion in the second quarter. To put its more than 30 trillion vision in context, the 191 technology companies in the S&P 1500 brought in 2.4 tri
arXiv:2602.13739v2 Announce Type: replace Abstract: Mobile robotic gas distribution mapping (GDM) provides critical situational awareness during emergency responses to hazardous gas releases. However,
arXiv:2608.22758v1 Announce Type: cross Abstract: Standard decoding rules for autoregressive language models promote diversity by rescaling the full next-token distribution or truncating its low-proba
arXiv:2601.15380v2 Announce Type: replace-cross Abstract: We generalize the attention mechanism by viewing it through the lens of Entropic Optimal Transport, revealing that standard attention correspo
arXiv:2608.22852v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific inve
arXiv:2603.14254v2 Announce Type: replace Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods
Source of Claims: https://x.com/Andy_ShuoYang/status/2090856976880472439 Your gaming PC can now serve frontier models at interactive speed using official checkpoints without extreme quantization! Qwen
arXiv:2608.20890v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for end-to-end autonomous driving by jointly integrating perception, reasoning,
arXiv:2608.20980v1 Announce Type: new Abstract: Graph neural networks (GNNs) are routinely employed for short-range forecasting on multivariate time series with a spatial graph structure. Despite the
arXiv:2608.20608v1 Announce Type: new Abstract: Grape leaf disease recognition is important for precision agriculture, enabling early diagnosis, timely intervention, and improved vineyard management.
arXiv:2603.28200v2 Announce Type: replace-cross Abstract: Guiding collective motion in biological groups is a fundamental challenge in understanding social interaction rules. In this study, we propose
arXiv:2608.20394v1 Announce Type: cross Abstract: Industry pipelines that turn speech into supervised fine-tuning (SFT) data via multi-stage refinement are increasingly adopted but, to our knowledge,
arXiv:2608.20367v1 Announce Type: cross Abstract: Poultry production operates under tightly coupled environmental and biological dynamics, yet commercial climate control remains largely heuristic, lim