Knowledge catalogue
arXiv:2510.03136v2 Announce Type: replace Abstract: Confidence calibration, the alignment of a model's predicted confidence with its actual accuracy, is crucial for the reliable deployment of Large La
CommerceAgentBench starts with real commercial demand, and Qwen3.8-Max delivers the strongest overall performance among open-weight models. Let's test Qwen on your real-world workflows! 🔥 Most AI benc
arXiv:2310.02423v3 Announce Type: replace Abstract: We present a new algorithm for amortized inference in sparse probabilistic graphical models (PGMs), which we call Delta-amortized inference (Delta-A
arXiv:2603.18007v2 Announce Type: replace-cross Abstract: The study explores whether current Large Language Models (LLMs) exhibit Theory of Mind (ToM) capabilities -- specifically, the ability to infe
arXiv:2608.28833v1 Announce Type: new Abstract: While Large language models (LLMs) incorporate user personalization signals to improve usability and helpfulness, they increasingly shift from providing
arXiv:2608.30439v1 Announce Type: cross Abstract: Inference with transformer-based large language models (LLMs) is often limited by the memory-bound KV cache and quadratic attention cost. State-space
arXiv:2608.29395v1 Announce Type: new Abstract: Vision-language models such as CLIP and SigLIP provide strong zero-shot recognition, but their predictions can degrade when deployed on target data that
arXiv:2603.28301v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models achieve strong performance in robotic manipulation by leveraging pre-trained vision-language backbones. However,
arXiv:2608.28701v1 Announce Type: new Abstract: Diagram-to-graph topology extraction aims to extract a graph of entities and their connections from a structural diagram. This task remains challenging
arXiv:2601.13247v2 Announce Type: replace Abstract: Current Large Language Models (LLMs) exhibit a critical modal disconnect: they possess vast semantic knowledge but lack the procedural grounding to
arXiv:2608.28053v1 Announce Type: new Abstract: Chinese neologisms exploit diverse and unique linguistic mechanisms, such as phonetic substitution (e.g., 886 for ``bye-bye'') and visual character deco
I've made a modification of llama.cpp MTP for people that want to run models like QWEN 27B on 16GB and similar setup, the focus is reducing the memory cost of MTP allowing more speed for less ctx cost
arXiv:2505.15450v3 Announce Type: replace Abstract: Text-to-image diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the
arXiv:2206.09012v4 Announce Type: replace-cross Abstract: We consider the problem of inferring high-dimensional data mathbf{x} in a model that consists of a prior p(mathbf{x}) and an auxiliary differe
arXiv:2509.19212v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in real-world applications, yet their ability to make context-aware safety decisi
arXiv:2608.28170v1 Announce Type: new Abstract: Purpose - This study investigates the feasibility of restoring missing text caused by physical lacunae in damaged ancient manuscripts using language mod
arXiv:2608.27578v1 Announce Type: cross Abstract: Training effective foundation models requires massive and organized datasets, yet scientific domains such as nuclear fusion present unique challenges
arXiv:2608.28549v1 Announce Type: new Abstract: Recent generative approaches to geometry estimation adapt pretrained image diffusion models and treat the task as image-conditioned generation. Leveragi
We’re ending our partnership with Cursor following its acquisition by SpaceX. Under our proposal, Cursor’s direct access to our models would end on November 12. We know that the people most affected b
arXiv:2608.26140v1 Announce Type: new Abstract: Diffusion Large Language Models (DLLMs) enable non-autoregressive decoding and bidirectional context modeling, but efficient inference remains challengi
arXiv:2608.26143v1 Announce Type: cross Abstract: Memes have turned out to be a powerful tool through which individuals share their ideas concerning contemporary social and political problems. Their a
arXiv:2608.27268v1 Announce Type: new Abstract: Although Large language models (LLMs) mediate access to knowledge and computational assistance, their capabilities should benefit vulnerable groups in t
A federal court has overturned the U.S. Defense Department’s ban on Anthropic PBC’s artificial intelligence models. Judge Rita Lin wrote in a late Thursday ruling that the Pentagon’s move was “illegal
arXiv:2608.26131v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed to serve open-ended, multi-turn interactions, evaluating conversational quality at human scale
arXiv:2608.26804v1 Announce Type: cross Abstract: Recommendation impressions are a finite resource, hence delivering a recommendation to a user who would discover the content organically yields no inc
arXiv:2608.27165v1 Announce Type: new Abstract: Autoregressive large language models (LLMs) routinely generate factually incorrect outputs with high decoding confidence, limiting their deployment in h
arXiv:2608.26239v1 Announce Type: new Abstract: Generative world models provide robots with predictive models of how the world evolves under interaction, with growing potential for simulation, plannin
arXiv:2608.26187v1 Announce Type: cross Abstract: Whether large language models (LLMs) can perform the abductive leap from evidence to a new system of axioms, commonly referred to as a jump, has recen
arXiv:2608.25190v1 Announce Type: new Abstract: Fake news detection has become an important Natural Language Processing (NLP) task due to the rapid spread of misinformation through online news platfor
Repost because reddit keeps thinking this is piracy or illegal. It is neither. A lot of people are skeptical Nvidia will keep huggingface intact now that they will buy huggingface. There's a lot of do
arXiv:2608.25976v1 Announce Type: new Abstract: International adoptees retain phonological traces of a birth language they can no longer speak or comprehend, a persistence typically attributed to a bi
arXiv:2608.26043v1 Announce Type: new Abstract: Multi-norm adversarial defense aims to protect neural networks against perturbations defined by different norm constraints, but existing methods typical
Just noticed this today. I've been trying to be careful to not max out my pro budget, but alas I am just a fool. Anyway, just noticed these free models. Some of these are pretty high in terms of compu
A lot of people are skeptical Nvidia will keep huggingface intact now that they will buy huggingface. There's a lot of doom and gloom about not having any alternatives, removing nsfw models, saying th
arXiv:2608.25555v1 Announce Type: new Abstract: Explainability for transformer-based language models is becoming crucial as these systems are deployed in high-stakes applications. As a result, the eco
arXiv:2601.00282v2 Announce Type: replace-cross Abstract: Quantization is widely used to accelerate inference and streamline the deployment of large language models (LLMs), yet its effects on self-exp
arXiv:2504.18346v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have been transformative across many domains. However, hallucination, i.e., confidently outputting incorrect info
arXiv:2608.23837v1 Announce Type: new Abstract: Large language models (LLMs) are known to exhibit social sycophancy, often validating or agreeing with users in socially sensitive contexts. Existing ev
arXiv:2601.16520v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in visual recognition and semantic understanding, yet precise compo
arXiv:2608.22187v1 Announce Type: cross Abstract: Modern driving action models are increasingly improved in a self-improvement loop, where a learned world simulator imagines future observations and th
arXiv:2608.22753v1 Announce Type: new Abstract: Large language models (LLMs) excel at text understanding and generation, yet still struggle to reliably understand and apply externally provided procedu
arXiv:2608.01033v2 Announce Type: replace-cross Abstract: Language models small enough to run on a handset, quantized to a few bits, are increasingly capable of acting on their user's behalf -- which
arXiv:2608.22483v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly support decision-making in high-stakes domains, but they often hallucinate and express confidence that is misa
arXiv:2608.22092v1 Announce Type: new Abstract: Reinforcement-learning models commonly predict complete future states, observations, or feature occupancies, even though action selection depends only o
arXiv:2608.23244v1 Announce Type: cross Abstract: Large language models (LLMs) often produce fluent but incorrect answers with unwarranted confidence. A central limitation is that standard LLMs repres
arXiv:2608.22824v1 Announce Type: new Abstract: Membership inference attacks expose whether individual records were used to train a model, yet existing attacks on diffusion models are largely heuristi
arXiv:2608.21827v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved significant progress across a wide range of natural language processing (NLP) tasks, yet their ability to und
arXiv:2608.21621v1 Announce Type: new Abstract: In on-device NLP tasks, limited resources of embedded hardware, such as the Raspberry Pi 5, require efficient inference strategies. This paper introduce
arXiv:2412.00776v5 Announce Type: replace Abstract: Continual learning (CL) learns from a non-stationary data stream without storing or re-training on all seen samples. Meta-continual learning (MCL) c
arXiv:2508.07173v3 Announce Type: replace Abstract: Omni-modal Large Language Models (OLLMs) that integrate visual, auditory, and textual processing face severe safety risks. They exhibit fragile defe
arXiv:2608.23475v1 Announce Type: new Abstract: As large language models are increasingly used in data-scarce and evolving task scenarios, few-shot in-context learning (ICL) has become a key paradigm
Share what your favorite models are right now and why. Given the nature of the beast in evaluating VLMs (untrustworthiness of benchmarks, immature tooling, intrinsic stochasticity), please be as detai
arXiv:2608.20483v1 Announce Type: cross Abstract: We develop analytical and particle-based methods for uncertainty propagation in random neural network models, where both the inputs and network parame
I recently implemented a minimal, educational version of SynthID-Text-style watermarking for language models. I saw anthropic post about how they'll start adding watermarks to their model responses an
Brace yourselves. We just entered a new era of frontier multimodal models. DeepSeek-V4-Flash-Vision-Exp advances multimodal agent performance. Also, pay attention to Ox Alpha 1M token contexts with te
arXiv:2606.23487v2 Announce Type: replace Abstract: Medical vision-language models (VLMs) such as BiomedCLIP generalize broadly, but adapting them to a clinical service is as much a safety problem as
arXiv:2608.20183v1 Announce Type: new Abstract: Classical information criteria such as the Bayesian Information Criterion (BIC) rely on regularity assumptions that break down for singular models, lead
arXiv:2606.18632v2 Announce Type: replace Abstract: Embodied Foundation Models (EFMs) integrate multimodal understanding, future-state reasoning, and executable robot actions. Yet their safety alignme
arXiv:2608.20237v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) combine linguistic reasoning with visual perception, yet their ability to perform visual spatial planning under
Congratulations to the whole @GoogleDeepMind Gemma team! Gemma is one of the most popular open models. It's been an amazing journey being a close partner! Can't wait to see what's to come! 🎉 Gemma off