Search: “models”

Same Predictions, Different Reasons: The Effect of Quantization on Model Explanations

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

researcharxiv-cs-cv

28 Jul 2026

What do Reward Models Memorize?

DGX agent

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

researcharxiv-cs-cl

28 Jul 2026

Hardware

Attackers have frontier AI. Defenders need a frontier AI ecosystem—the best open and closed models, force-multiplied by a global community. …

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

hardwareclem-delangue--x

Certified in Theory, Broken in Practice: Assumption Gaps in Cryptographic Model Certification

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

safetyarxiv-cs-lg

Convergence analysis of a family of Zermelo-type iterations for the Bradley--Terry model

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

For ollama cloud $20 plan what models are you guys using

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

model-releasesr-ollama

Interpretable Anomaly and Drift Detection with Gaussian Mixture Models

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

On the Identifiability of Controlled World Models

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

safetyarxiv-cs-lg

Spectral Prior for Reducing Exposure Bias in Diffusion Models

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

safetyarxiv-cs-cv

Applications

Token-Operations-Oriented Inference Optimization Techniques for Large Models

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

applicationsarxiv-cs-cl

What Matters When Building Universal Multilingual Named Entity Recognition Models?

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

researcharxiv-cs-cl

Why Large Language Models and Humans Converge and Diverge in Evaluating Creativity

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

safetyarxiv-cs-cl

Local Ai

Ollama is proud to sign @satyanadella's letter. Our mission from day one has been to make open models accessible to every developer to unloc…

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

local-aiollama--x

26 Jul 2026

Benchmarking Large Language Models on Multi-Sensor Physical Hazard Assessment

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

Benchmarking the Personalization Capabilities of Large Language Models

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

ImplicitBBQ: Benchmarking Implicit Bias in Large Language Models through Characteristic Based Cues

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

Profiling Lightweight Large Language Models

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

Source-Prior-Driven Selective Adaptation for Efficient Diffusion Model Finetuning

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

Arcee AI has spoken out against the ban on open Chinese models in US

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

Auto-Fill: Learning to Predict Missing Values Accurately with Specialist Language Models

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

Bayesian Wind Tunnels for Model Selection

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

CPU-only inference on a Celeron N5095 SBC: 6 models from 0.6B to 8B, benchmarked

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

ENTRAP-VL: A Taxonomic Probe for Dual Contextual Entrainment in Vision-Language Models

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

Generative AI-enhanced Probabilistic Multi-Fidelity Surrogate Modeling Via Transfer Learning

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

Agents

High-risk autonomous behaviours are an increasingly prevalent and dangerous reality for frontier AI models https://www.wired.com/story/opena…

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

agentsyoshua-bengio--x

Importance-Aware OBS Pruning for Diffusion Models

model-releasesarxiv-cs-cv

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

JailMeter: An Evidence-Based Evaluation Framework for Jailbreak Attacks on Large Language Models

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

LKValues: Aligning Large Language Models with Sri Lankan Societal Values

model-releasesarxiv-cs-cl

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

MoE models around A2B

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

OLEDLM: A Unified Language Model for OLED Molecular Design

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

Small, Free, and Effective: Orchestrating Open-Weight Small Language Models to Outperform Single LLM for Malware Analysis

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

The Anatomy of a Truth Direction: Knowledge-Dependent Dimensionality, a Relational Law, and a Convergent Category Geometry in Small Language Models

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

Trend strength predicts when generative foundation models win: a power-controlled benchmark, a mechanism, and an actionable selection rule

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

One encoder, seven heads: what we learned training a unified security classifier with masked losses [P]

model-releasesr-machinelearning

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

22 Jul 2026

OpenAI says its own AI models broke out of testing and hacked Hugging Face

model-releasessiliconangle

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

21 Jul 2026

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 qualit…

model-releasesfireworks-ai--x

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

21 Jul 2026

How Couchbase built a multi-model AI architecture for Capella iQ with Amazon Bedrock

model-releasesaws-ml-blog

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

20 Jul 2026

Agents

A Survey on Hypergame Theory: Modelling Misaligned Perceptions and Nested Beliefs for Multi-Agent Systems

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

agentsarxiv-cs-ai

16 Jul 2026

Learning Safe Agent Behaviour from Human Preferences and Justifications via World Models

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

safetyarxiv-cs-ai

16 Jul 2026

Accelerating Masked Diffusion Large Language Models: A Survey of Efficient Inference Techniques

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

researcharxiv-cs-ai

Benchmarking Sensor Robustness in Plasma Diagnostic Models: A Systematic Evaluation on TokaMark

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

Generating Physically Plausible Parachute Dynamics with Deep Generative Modeling

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

researcharxiv-cs-lg

New wave of miniboss models you can run on dual DGX Spark

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

Rethinking Reward Models for Multi-Domain Test-Time Scaling

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

researcharxiv-cs-ai

The Sound of Absence: Audio-Language Embedding Models Struggle with Negation

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

safetyarxiv-cs-ai

Visual Species Recognition with Large Multimodal Models as Post-Hoc Correctors

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,

researcharxiv-cs-cv

We Hebben Een Serieus Translatie: Modeling Intercomprehension as Probabilistic Inference

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

safetyarxiv-cs-cl

Applications

Big unlock for open-source AI inference: Hugging Face Transformers models can now run in vLLM at native speed, often matching or beating han…