Knowledge catalogue
arXiv:2602.01034v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a widely used paradigm for improving the reasoning abilities of large language models (LLMs) and Vision-langu
Voice artificial intelligence startup Modulate Inc. today announced it has raised 25 million in new funding to get its audio-native models in front of more developers. Modulate offers AI models that w
🛠️ MiMo-V2.6 update: tool-call repetition, diagnosed & fixed. After the MiMo-V2.6 series models launched, we noticed them sometimes repeating identical or highly similar tool calls — burning context a
As reports of OpenAI's models breaking containment, hacking sites, and generally getting out of control pile up, the company has made the decision to pause training of its most powerful models. The de
This Week in Replit 1) Three new models in Replit Agent: GPT-6 Sol, GPT-6 Luna Fast, and Claude Opus 5.5. Experiment with them and see how they fit your flow. 2) Muse can now make apps in Replit. Repl
arXiv:2609.28998v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) has become a popular parameter-efficient fine-tuning method for large language models. A key challenge in LoRA is how to dete
arXiv:2609.28811v1 Announce Type: new Abstract: World-action models (WAMs) transfer visual and motion priors from pretrained video generators to robot control by jointly modeling visual dynamics and a
arXiv:2609.28692v1 Announce Type: new Abstract: Artificial Intelligence agents based on large language models provide convenient natural language interfaces to scientific software, but reliability is
arXiv:2609.30218v1 Announce Type: cross Abstract: Pre-logit steering adapts a frozen language model to a test-time reward by adding vectors to its final hidden states. Unregularized reward optimizatio
arXiv:2609.29835v1 Announce Type: new Abstract: LiDAR provides precise geometric information for spatial perception tasks such as object detection in autonomous driving and outdoor robotics. However,
arXiv:2609.28778v1 Announce Type: cross Abstract: Audio-language models (ALMs) can exploit textual shortcuts to answer questions while overlooking acoustic evidence, weakening audio understanding. On-
Been dealing with the same thing a lot of people here probably are - RAM prices keep climbing and buying a single machine with enough memory for the models I actually want to run just isn't realistic
arXiv:2609.27234v1 Announce Type: new Abstract: AI virtual cells aim to predict cellular responses to specified interventions, yet held-out predictive performance alone does not establish use of the s
arXiv:2609.27233v1 Announce Type: new Abstract: Transformer language models process sequences token by token in an autoregressive manner, making growing contexts increasingly expensive. Yet many adjac
arXiv:2609.28231v1 Announce Type: cross Abstract: Pathology foundation models (PFMs) have transformed computational pathology through powerful representation learning from histopathological images. PF
arXiv:2609.27581v1 Announce Type: cross Abstract: Step Law gives power-law formulas for the optimal peak learning rate eta* and batch size B* when pre-training language models. It was calibrated on mo
arXiv:2609.27678v1 Announce Type: new Abstract: Contract inference requires multiple judgments about a shared document, but aggregate accuracy can conceal changes in the individual decisions. Repeated
The applications of new world models like Agora-2 are mind-blowing. Agora-2 now lets up to 20 humans and agents share one simulated world in real time. That means you can train robots, self-driving ca
10,000 OpenAI agents worked 88 hours on the Navier-Stokes Clay prize problem Alas, open models fall off hard on long tasks With Zenith, @deepseek_ai's V4.1 Flash reaches the frontier & beats GPT-5.6 S
arXiv:2410.07421v2 Announce Type: replace Abstract: Instance segmentation is a core computer vision task with great practical significance. Recent advances, driven by large-scale benchmark datasets, h
arXiv:2609.25447v1 Announce Type: new Abstract: We study what LLMs do when a user applies pressure in an uncomfortable situation: a user insists, begs, flatters or grieves, and the model gives up a co
arXiv:2609.24346v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) has remarkably enhanced large language models on complex reasoning by leveraging structured entity topol
arXiv:2406.04814v4 Announce Type: replace-cross Abstract: Video diffusion models can enable embodied agents to anticipate plausible futures from the recent past, but they are typically trained offline
arXiv:2609.25444v1 Announce Type: new Abstract: This work studies prediction parameterization for stochastic generative dynamics in diffusion models. Existing velocity-based generative models provide
arXiv:2510.21175v2 Announce Type: replace Abstract: Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated remarkable zero-shot generalization, enabling deployment in a wide range
On stage with @MistralAI . 🔥 From building models to putting them into the hands of developers, a closer look at how Mistral is shaping the next generation of AI products. Straight from the #AIEParis
arXiv:2609.25890v1 Announce Type: new Abstract: Short-to-long training is a simple curriculum for speech models, but its gains can be difficult to interpret. In speech token language models, length-ba
The new Gemini 3.8 TTS models are super-cheap and can generate conversations between multiple voices (from 2,000+, or you can clone your own) - I built a little UI for it, then had Claude knock up a s
Pair OpenCode, an open-source terminal-native AI coding agent, with open weight models on Amazon Bedrock to get a secure, flexible, pay-per-use coding assistant. Learn how to configure multi-model wor
We’re demonstrating how frontier models have continued to improve in realistic mental health conversations with MentalHealthBench. This new open benchmark was built with input from more than 80 mental
arXiv:2609.22154v1 Announce Type: new Abstract: Tabular data is the most common format in clinical practice, encompassing laboratory results, medication records, diagnostic codes, and patient demograp
arXiv:2511.18921v2 Announce Type: replace Abstract: Backdoor attacks undermine the reliability and trustworthiness of machine learning systems by injecting hidden behaviors that can be maliciously act
arXiv:2609.23650v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved strong performance in embodied manipulation, but still lack a clear mechanism to balance behavioral
arXiv:2609.24276v1 Announce Type: new Abstract: Hyperbolic vision-language models (VLMs) represent image and text features in a geometry naturally suited to hierarchy, but their adaptation to downstre
arXiv:2609.22152v1 Announce Type: new Abstract: Imagination performs as a high-level function of large language models (LLMs) which determines the potential of how an LLM creates unseen or creative co
arXiv:2609.22867v1 Announce Type: new Abstract: Diffusion models generate a sample by traversing a denoising trajectory, a sequence of stochastic noise-reduction steps that transforms pure noise into
arXiv:2609.23924v1 Announce Type: new Abstract: Pretrained EEG foundation models are increasingly proposed as general-purpose encoders for brain-computer interfaces, yet recent benchmarks disagree abo
arXiv:2609.23574v1 Announce Type: cross Abstract: In high-dimensional tabular learning, feature screening provides a lightweight, model-agnostic way to remove irrelevant features before model fitting.
arXiv:2609.23600v1 Announce Type: new Abstract: Prompt learning efficiently adapts vision-language models (VLMs) to downstream tasks, but gains on seen classes often come at the expense of generalizat
arXiv:2609.24057v1 Announce Type: cross Abstract: Medical image interpretation is central to diagnosis and care, yet adapting general-purpose multimodal large language models (MLLMs) often requires re
arXiv:2609.23016v1 Announce Type: cross Abstract: Deep learning models are powerful but opaque. As quantum machine learning matures, the field faces a defining choice: build quantum models that are eq
arXiv:2609.21666v1 Announce Type: cross Abstract: The success of Large Audio Language Models has driven the development of massive multimodal networks exceeding billions of parameters. However, the de
arXiv:2609.20386v1 Announce Type: new Abstract: Iris presentation attack detection (PAD) is security-critical when a subsystem that appears reliable during development encounters presentation attack i
arXiv:2602.00141v2 Announce Type: replace-cross Abstract: Quark-gluon discrimination provides a useful test case for studying how different machine-learning architectures learn the spatial structure o
arXiv:2609.19674v1 Announce Type: new Abstract: A learned simulator can reproduce its training conditions accurately yet fail in two distinct ways once those conditions change. Over long rollouts, sma
arXiv:2609.20649v1 Announce Type: cross Abstract: Learning predictive models of contact-rich dexterous manipulation requires dense tactile interaction, but such data are costly to scale on real robots
arXiv:2609.20751v1 Announce Type: new Abstract: Adapting a pretrained autoregressive (AR) model is a cost-efficient route to a diffusion language model (DLM). While nearly all such adaptations start f
arXiv:2609.19445v1 Announce Type: cross Abstract: The rapid expansion of multimodal models has surfaced formidable bottlenecks in computation, memory, and deployment, catalyzing the rise of Efficient
arXiv:2609.19315v1 Announce Type: cross Abstract: Large language models (LLMs) provide a flexible interface for long-horizon robot planning, but generated plans often fail to respect embodiment constr
I had Astra run a multi-hour investigation into speeding up local MoE inference while keeping the model weights and quantization unchanged. The experiments covered Qwen3.6-35B-A3B and Qwen3.8 Flash-Ne
arXiv:2609.20195v1 Announce Type: cross Abstract: Audio-language models increasingly generate confident music descriptions that are unsupported by the input audio. We present, to our knowledge, the fi
arXiv:2609.20734v1 Announce Type: new Abstract: Reasoning and agentic workloads increasingly demand efficient long-context inference. Yet full-attention decoding reads the growing history at every ste
arXiv:2609.19441v1 Announce Type: cross Abstract: World action models (WAMs) rely on video-generation backbones, requiring substantial memory and compute for deployment. Post-training quantization red
arXiv:2602.03449v2 Announce Type: replace-cross Abstract: Score-based diffusion models are a recently developed framework for posterior sampling in Bayesian inverse problems, enabling high-quality rec
arXiv:2609.19592v1 Announce Type: new Abstract: This study developed and evaluated a deep-learning-based perception framework for selective robotic cotton picking. The dataset contained 1,008 annotate
arXiv:2609.20077v1 Announce Type: new Abstract: Interest in developing personalised language models is rapidly growing. While personalisation is often viewed as a mechanism to better serve diverse use
Yael Grauer / The Verge: Anthropic and other researchers detail how thousands of people were catfished by dating scam apps using LLM-generated replies from Claude and other models — Security researche
arXiv:2609.18320v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently exhibit hallucinations, presenting a major barrier to reliability in complex reasoning tasks. While traditional
arXiv:2609.18130v1 Announce Type: cross Abstract: Surrogate-assisted evolutionary algorithms (SAEAs) are effective methods for solving expensive optimization problems (EOPs), where surrogate models re
Why evaluating image editing models is both critical and challenging Instruction-based image editing is becoming a core capability of multimodal foundation models. Users can increasingly edit images s