Knowledge catalogue
arXiv:2604.18751v1 Announce Type: cross Abstract: Nonlinear machine-learning models are increasingly used to discover causal relationships in time-series data, yet the interpretation of their outputs
arXiv:2604.00688v3 Announce Type: replace Abstract: We present OmniVoice, a massively multilingual zero-shot text-to-speech (TTS) model that scales to over 600 languages. At its core is a novel diffus
arXiv:2510.24942v2 Announce Type: replace-cross Abstract: Despite their impressive performance, vision-language models (VLMs) still struggle on culturally situated inputs. To understand how VLMs proce
arXiv:2604.17941v1 Announce Type: cross Abstract: Recent work has increasingly explored neuron-level interpretation in vision-language models (VLMs) to identify neurons critical to final predictions.
arXiv:2604.17930v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit a puzzling disparity in their formal linguistic competence: while they learn some linguistic phenomena with near-pe
arXiv:2604.16378v1 Announce Type: new Abstract: Large language models (LLMs) and classical machine learning methods offer complementary strengths for predictive modeling, yet their fundamentally diffe
arXiv:2603.05863v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have revolutionized code generation, standard ``System 1'' approaches that generate solutions in a single forward
arXiv:2508.11281v3 Announce Type: replace Abstract: Detecting toxic content using language models is crucial yet challenging. While substantial progress has been made in English, toxicity detection in
arXiv:2511.17699v2 Announce Type: replace Abstract: Counting is one of the fundamental abilities of large language models (LLMs) and large vision-language models (LVLMs). This paper examines how these
arXiv:2604.16241v1 Announce Type: cross Abstract: Large language models have shown strong performance on broad-domain knowledge and reasoning benchmarks, but it remains unclear how well language model
arXiv:2604.16280v1 Announce Type: new Abstract: Explaining Machine Learning (ML) results in a transparent and user-friendly manner remains a challenging task of Explainable Artificial Intelligence (XA
arXiv:2505.11017v2 Announce Type: replace Abstract: Time series forecasting is critical across multiple domains, where time series data exhibit both local patterns and global dependencies. While Trans
Been having fun with local AI stuff. I don't really like the big models and now that some of them want your ID I'm not sure I'll even stick around to care that much. Local shit is really powerful now,
arXiv:2604.13413v1 Announce Type: new Abstract: Diffusion language models (DLMs) have emerged as a promising paradigm for large language models (LLMs), yet the non-deterministic behavior of DLMs remai
arXiv:2603.19790v3 Announce Type: replace Abstract: Modern vision-language models (VLMs) can act as generative OCR engines, yet open-ended decoding can expose rare but consequential failures. We ident
arXiv:2604.05478v2 Announce Type: replace-cross Abstract: Immune checkpoint inhibitors (ICIs) have transformed cancer therapy; yet substantial proportion of patients exhibit intrinsic or acquired resi
arXiv:2510.13793v2 Announce Type: replace Abstract: With the rapid adoption of diffusion models for visual content generation, proving authorship and protecting copyright have become critical. This ch
arXiv:2509.18127v3 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) enable interpretability research by decomposing entangled model activations into monosemantic features. However, un
And this is a very generous definition of notable. If we are talking frontier models, only the US and China that are even in the race. And that obscures the fact that the Big Three US labs really do s
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:2510.09389v2 Announce Type: replace-cross Abstract: Deep sequence models, ranging from Transformers and State Space Models (SSMs) to more recent approaches such as gated linear RNNs, fundamental
arXiv:2604.10690v1 Announce Type: new Abstract: Foundation models have shown remarkable performance across diverse tasks, yet their ability to construct internal spatial world models for reasoning and
arXiv:2604.10200v1 Announce Type: new Abstract: As Vision-Language Models (VLMs) become integral to educational decision-making, ensuring their fairness is paramount. However, current text-centric eva
arXiv:2604.09741v1 Announce Type: cross Abstract: For large language models deployed through black-box APIs, recurring inference costs often exceed one-time training costs. This motivates composed age
arXiv:2603.22911v2 Announce Type: replace-cross Abstract: Due to the great saving of computation and memory overhead, token compression has become a research hot-spot for MLLMs and achieved remarkable
arXiv:2601.03416v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have become widely deployed, yet their safety alignment remains fragile under adversarial inputs. Previous
arXiv:2603.18893v2 Announce Type: replace Abstract: Tracking the internal states of large language models across conversations is important for safety, interpretability, and model welfare, yet current
arXiv:2604.10299v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) rely on attention-based retrieval of safety instructions to maintain alignment during generation. Existing attack
arXiv:2603.21942v2 Announce Type: replace-cross Abstract: We introduce Suiren-1.0, a family of molecular foundation models for the accurate modeling of diverse organic systems. Suiren-1.0 comprising t
arXiv:2602.14200v4 Announce Type: replace Abstract: Time Series Language Models (TSLMs) are emerging as unified models for reasoning over continuous signals in natural language. However, long-context
if you bounce between claude code and codex, that’s completely normal. the models are good at different things and everyone's workflow is dynamic but you’re also paying multiple subscriptions, constan
arXiv:2604.07814v1 Announce Type: new Abstract: Accurate and interpretable plant disease diagnosis remains a major challenge for vision-language models (VLMs) in real-world agriculture. We introduce A
arXiv:2604.06946v1 Announce Type: cross Abstract: Automated test case generation from natural language requirements remains a challenging problem in software engineering due to the ambiguity of requir
arXiv:2509.23322v2 Announce Type: replace Abstract: With the continuous expansion of Large Language Models (LLMs) and advances in reinforcement learning, LLMs have demonstrated exceptional reasoning c
arXiv:2604.06465v1 Announce Type: cross Abstract: Reasoning models have demonstrated remarkable capabilities in solving complex problems by leveraging long chains of thought. However, this more delibe
arXiv:2604.06814v1 Announce Type: cross Abstract: While traditional tree-based ensemble methods have long dominated tabular tasks, deep neural networks and emerging foundation models have challenged t
arXiv:2604.08238v1 Announce Type: new Abstract: The increasing adaptation of vision models across domains, such as satellite imagery and medical scans, has raised an emerging privacy risk: models may
arXiv:2604.08120v1 Announce Type: cross Abstract: Adapting Multimodal Large Language Models (MLLMs) for hour-long videos is bottlenecked by context limits. Dense visual streams saturate token budgets
arXiv:2604.07102v1 Announce Type: cross Abstract: Activation-based steering can personalize large language models at inference time, but its effects in educational settings remain unclear. We study pe
arXiv:2604.07957v1 Announce Type: cross Abstract: Vision-language models (VLMs) and generative world models are opening new opportunities for embodied navigation. VLMs are increasingly used as direct
The specific tweet from @0xSero is not directly accessible, and the search results don't surface the exact model or event being referenced in that post. However, based on the context clues in the t...
arXiv:2610.20785v1 Announce Type: new Abstract: Large language models are increasingly used in social interactions, where appropriate responses require recognizing implicit cues, inferring mental stat
K3 came out in July hyped as the best open model you could download, and it scored 57 on Artificial Analysis, right up there with Opus 4.8 and GPT-5.5. I went back to see what running it actually look
arXiv:2610.20951v1 Announce Type: new Abstract: Decision models answer typed questions about an input with one probability per option, computed in a single forward pass without generating text. Like t
arXiv:2610.21230v1 Announce Type: new Abstract: Unlearning aims to remove selected knowledge from large language models to mitigate privacy and safety risks while preserving useful capabilities. For m
arXiv:2610.20808v1 Announce Type: new Abstract: Recent literature shows that unsafe tool calls can often accompany textual refusals in language models. To investigate this hidden vulnerability, we int
arXiv:2610.20824v1 Announce Type: cross Abstract: Wolof is spoken by 23M people, mostly in Senegal, but remains weakly supported by open-weight language models, while API models raise cost, governance
arXiv:2512.22814v2 Announce Type: replace Abstract: Accurate long-range weather forecasting remains a major challenge for AI models, both because errors accumulate over autoregressive rollouts and bec
arXiv:2503.21821v2 Announce Type: replace Abstract: We introduce Physics, a benchmark for evaluating foundation models on advanced physics problem solving. It contains 1034 annotated, open-ended probl
arXiv:2610.14299v1 Announce Type: cross Abstract: Recent Speech Full-Duplex (FDX) models are capable of engaging in naturalistic conversation by listening and speaking at the same time. Building on th
arXiv:2610.14443v1 Announce Type: cross Abstract: Model cards, system cards, and safety reports increasingly document LLM safety behaviors, yet safety evaluations typically start from predefined bench
arXiv:2610.19407v1 Announce Type: new Abstract: Vision-language models must reconcile conflicting text and images. Prior work has characterized the resulting behavior in terms of modality biases--e.g.
Anthropic cautions that lightweight AI models—requiring far less compute than frontier models—could soon gain the ability to self‑replicate across Internet‑of‑Things devices, creating new autonomous w
arXiv:2610.14014v1 Announce Type: new Abstract: Accurate day-ahead photovoltaic (PV) power forecasting requires both strong temporal modeling and adherence to physical PV system constraints. Purely da
arXiv:2610.17590v1 Announce Type: new Abstract: Diffusion language models (DLMs) have attracted wide attention for their fast, parallel decoding, but they are believed to be far less efficient to trai
arXiv:2610.18697v1 Announce Type: cross Abstract: World models (WMs) and world-action models (WAMs) focus on future world prediction and executable action generation, respectively. Although these mode
arXiv:2610.14007v1 Announce Type: new Abstract: A familiar line of reasoning runs as follows: language models are flexible approximators trained under a strictly proper loss, so scale brings them clos
llama.cpp now has a Windows app 🦙 Llama Windows makes it easy to run models locally, with optimizations for NVIDIA RTX Spark. 📥 Browse and download models from Hugging Face 💬 Chat with local models ri
This is an update to my previous post which can be found here: https://www.reddit.com/r/LocalLLaMA/s/n7sgRZZc4z Since my last post I have continued working on the conversion process and also convertin
arXiv:2610.13948v1 Announce Type: new Abstract: Language models increasingly support or automate information retrieval from document collections too large to index. This task is difficult when it requ