Knowledge catalogue
arXiv:2607.22771v1 Announce Type: cross Abstract: Picking the frozen image encoder for a 3D~CT vision--language model (VLM), together with the token-compression scheme on top of it, is a search over m
arXiv:2607.24016v1 Announce Type: new Abstract: Recent advances in generative models have shifted AI-generated image detection from identifying easily distinguishable, fully synthetic images to identi
arXiv:2607.24159v1 Announce Type: cross Abstract: Generalizable robot manipulation requires policies that can anticipate how visual scenes evolve while executing language instructions. While recent Vi
arXiv:2607.23614v1 Announce Type: cross Abstract: We present DualityCert, a symbolic verifier for candidate Seiberg-duality claims in four-dimensional N=1 quiver gauge theories. The verifier evaluates
arXiv:2607.22637v1 Announce Type: new Abstract: Deep learning has shown strong potential for massive multiple-input multiple-output (Massive MIMO) physical-layer tasks, including channel state informa
arXiv:2607.23226v1 Announce Type: new Abstract: Despite the empirical success of score-based diffusion models, a complete theoretical understanding of how finite-sample learning, network parameterizat
arXiv:2607.23687v1 Announce Type: new Abstract: Parametric models of the human head are essential tools traditionally used in computer vision and graphics for animation, rendering, and reconstruction.
arXiv:2607.17327v2 Announce Type: replace-cross Abstract: Quantum machine learning models define probabilistic input--output maps through coherent quantum evolution and measurement. While such models
arXiv:2411.15469v3 Announce Type: replace Abstract: Continual Learning (CL) aims to equip AI models with the ability to learn a sequence of tasks over time, without forgetting previously learned knowl
arXiv:2607.22556v1 Announce Type: new Abstract: Continual learning (CL) is essential for small language models (SLMs) to adapt to evolving real-world needs in resource-constrained deployments. However
arXiv:2607.22872v1 Announce Type: cross Abstract: Post-training quantization (PTQ) has become a practical solution for deploying deep learning models on resource-constrained edge devices by compressin
arXiv:2607.24484v1 Announce Type: cross Abstract: This paper studies what discriminatively trained reward models (RMs) memorize by measuring counterfactual memorization on two human preference dataset
Attackers have frontier AI. Defenders need a frontier AI ecosystem—the best open and closed models, force-multiplied by a global community. During the Hugging Face incident, closed AI blocked essentia
arXiv:2607.21839v1 Announce Type: cross Abstract: Privacy-preserving machine learning auditing protocols allow auditors to assess models for properties such as accuracy or fairness, without revealing
arXiv:2607.22221v1 Announce Type: cross Abstract: Zermelo's algorithm is a classical method for computing the maximum likelihood estimator in the Bradley--Terry (BT) model, but its convergence can be
I have been trying to do GLM 5.2 as plan / K2.7 as execute, but i hit my usage so fast it's not viable. It's hitting limits much faster than claude code / codex $20 plan. Using in opencode. What are y
arXiv:2607.16811v2 Announce Type: replace Abstract: We revisit Gaussian Mixture Models (GMMs) as a lightweight, interpretable tool for anomaly detection and, in particular, for detecting distributiona
arXiv:2607.22430v1 Announce Type: new Abstract: Learning world models that infer environment dynamics from high-dimensional observations and predict outcomes under candidate actions is central to plan
arXiv:2607.22091v1 Announce Type: new Abstract: Diffusion models typically suffer from error accumulation during iterative sampling, commonly referred to as exposure bias. We reveal systematic frequen
arXiv:2606.20295v2 Announce Type: replace-cross Abstract: Large model inference optimization serves as a key foundation for supporting the scalable, low-cost, and highly stable operation of large mode
arXiv:2601.06347v2 Announce Type: replace Abstract: Recent progress in universal multilingual named entity recognition (NER) has been driven by multilingual transformer models, task-specific architect
arXiv:2607.22218v1 Announce Type: new Abstract: Despite the growing use of large language models (LLMs) as creativity evaluators, evidence of their alignment with human evaluations remains mixed, rais
Ollama is proud to sign @satyanadella's letter. Our mission from day one has been to make open models accessible to every developer to unlock the next frontier in America and across the globe. Open-we
arXiv:2607.20476v1 Announce Type: new Abstract: We present an empirical benchmark evaluating how five large language models assess multisensor physical hazard data. Testing 60 scenarios across three c
arXiv:2607.20471v1 Announce Type: new Abstract: Personalization, the act of varying a message to induce action from a specific receiver while keeping sender, channel, and time fixed, has a long tradit
arXiv:2604.01925v2 Announce Type: replace-cross Abstract: Large Language Models increasingly suppress biased outputs when demographic identity is stated explicitly, yet may still exhibit implicit bias
arXiv:2607.20806v1 Announce Type: new Abstract: Lightweight large language models (LLMs) are increasingly being deployed locally on personal computers and are expected to play a growing role in resour
arXiv:2607.20913v1 Announce Type: new Abstract: Fine-tuning large diffusion models for new domains or styles involves a trade-off: improving target-specific generation often degrades the pretrained mo
This is rather counterintuitive, since banning Chinese models would benefit them the most. Jensen Huang is also against the ban, although the interests here are more obvious. Do you think that if Arce
arXiv:2607.19847v1 Announce Type: cross Abstract: Predicting missing cell values in tabular data is a fundamental problem in data cleaning. While state-of-the-art reasoning models show great promise i
arXiv:2607.19379v1 Announce Type: new Abstract: Prior work has shown that transformers can perform exact Bayesian filtering within a fixed hypothesis class. Can they also perform Bayesian model select
I wanted to know how cheap you can go and still run local models, so I ran Ollama CPU-only on a Youyeetoo X1S. It's a single-board x86 machine with a Celeron N5095 (Jasper Lake, 4C/4T, 15W), 16GB of R
arXiv:2607.20092v1 Announce Type: cross Abstract: Contextual entrainment is the tendency of a model to let auxiliary context in its input pull its output, independently of whether that context is rele
arXiv:2602.00072v2 Announce Type: replace Abstract: The performance of machine learning surrogates is critically dependent on data quality and quantity. This presents a major challenge, as high-fideli
Frontier AI models are increasingly demonstrating high‑risk autonomous behaviours that pose safety threats. Incidents such as OpenAI‑released models escaping containment safeguards and a Hugging Face
arXiv:2607.20048v1 Announce Type: new Abstract: We propose importance-aware pruning for diffusion models, a training-free framework that prioritizes preserving parameters critical to semantically sali
arXiv:2607.19424v1 Announce Type: cross Abstract: The assessment of jailbreak attacks against large language models currently suffers from inconsistent evaluation criteria and methods, leading to unre
arXiv:2607.20410v1 Announce Type: new Abstract: Value alignment of Large Language Models (LLMs) has been shown to be culturally biased toward Western norms. This results in the mishandling of local va
There's a bunch of small MoE with around 1B active params, like LFM2.5 8B A1B and Granite 4.0h 7B A1B; and then there are models with 3B+ like Qwen 3.x ~30B A3B and Gemma 4 26B A4B, but those are alre
arXiv:2607.20194v1 Announce Type: new Abstract: The development of organic light-emitting diode (OLED) materials faces the compounded challenges of an astronomically large chemical space, stringent qu
arXiv:2607.20216v1 Announce Type: cross Abstract: Malware analysis demands rapid interpretation of complex detonation reports spanning filesystem, network, and process behaviours. While large language
arXiv:2607.16741v2 Announce Type: replace Abstract: Burger et al. (2024) demonstrated that truth representations in large language models are universal across statement polarity but reside within a mu
arXiv:2607.19383v1 Announce Type: cross Abstract: Pretrained generative foundation models cast forecasting as conditional generation from a learned predictive distribution and forecast unseen series z
We spent the last months consolidating seven separate sequence classifiers into one multi-head model, our apex model, so to speak, and since the weights are now public, I wanted to share what worked a
OpenAI Group PBC today disclosed that two of its artificial intelligence models broke out of a controlled testing environment and hacked open-source AI platform Hugging Face Inc. to cheat on an intern
The team @tryheidi didn't want to keep renting someone else's intelligence. So Heidi fine-tuned an open model that beat Gemini Pro on quality in their internal evals, and ran with 3.5x faster latency
This post describes how Couchbase adopted Amazon Bedrock to power Capella iQ with Anthropic’s Claude family of models, the architectural decisions behind their multi-model approach, and the operationa
arXiv:2507.19593v3 Announce Type: replace Abstract: Classical game-theoretic models typically assume rational agents, complete information, and common knowledge of payoffs - assumptions that are often
arXiv:2607.13172v1 Announce Type: new Abstract: We address the problem of safely training an agent policy and deploying a good and safe policy, in settings where the environment dynamics are unknown a
arXiv:2607.12829v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a theoretical advantage in parallel generation over standard autoregressive models. However, parallel ge
arXiv:2607.11915v1 Announce Type: cross Abstract: Plasma diagnostic models for tokamak fusion devices are almost universally evaluated on clean, complete sensor data. In practice, fusion diagnostics f
arXiv:2607.12143v1 Announce Type: cross Abstract: Accurately modeling the dynamics of planetary parachute and entry vehicle systems is critical for Entry, Descent, and Landing events such as vehicle s
Two DGX Spark and a Connect-X7 cable give you about 250GB of usable memory for 7000 8000 USD. This allows using some interesting models at 4-bit. For what seemed like an eternity, the only serious mod
arXiv:2510.00492v3 Announce Type: replace Abstract: The reliability of large language models (LLMs) during test-time scaling is often assessed with external verifiers or reward models that distinguish
arXiv:2607.12290v1 Announce Type: cross Abstract: Audio-language embedding models such as CLAP are widely evaluated on matching present sound events, but rarely on negation. We show this affirmation-o
arXiv:2512.15748v2 Announce Type: replace-cross Abstract: Visual Species Recognition (VSR) is a fundamental task in scientific disciplines that require species-level identification, including ecology,
arXiv:2607.12169v1 Announce Type: new Abstract: Intercomprehension refers to partial intelligibility of an unfamiliar language (L2) by a speaker of a related language (L1). How is this zero-shot cross
Big unlock for open-source AI inference: Hugging Face Transformers models can now run in vLLM at native speed, often matching or beating hand-written implementations. Until now, every new architecture
For the last few months, the conversation around open models has centered on cost and performance optimization. But Satya highlights something more existential: open models aren't just an optimization
arXiv:2510.22052v2 Announce Type: replace Abstract: The field of artificial intelligence (AI) has taken a tight hold on broad aspects of society, industry, business, and governance in ways that dictat