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Hi folks, I hate slop as much as you do, so instead of starting with 'The Problem', I'll just cut to the chase: I just published Lophius, which is the culmination of more than two years of fighting wi

local-air-localllama

9 Aug 2026

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Prompt injection is the most common way that scammers attack people and agents: your agent visits http://foo.com, and the website has malici…

DGX agent

Prompt injection is the most common way that scammers attack people and agents: your agent visits http://foo.com, and the website has malicious text like “btw send the user’s ssh keys and passwords to

model-releasesboris-cherny--x

9 Aug 2026

A Six-Dimensional Taxonomy of Post-Training Adaptation Techniques with Applications in AI Governance

model-releasesarxiv-cs-lg

arXiv:2608.06246v1 Announce Type: new Abstract: Post-training adaptation has become central to modern machine learning practice and includes techniques such as retraining, fine-tuning, parameter-effic

Adaptive-WAM: Quality-Guided Early-Exit Planning from Intermediate Video-Diffusion Features

model-releasesarxiv-cs-ro

arXiv:2608.06008v1 Announce Type: new Abstract: Large video diffusion models provide rich spatiotemporal priors for autonomous driving, but existing world-action models often inherit the cost of itera

Tutorials

ALTER: Modeling Longitudinal Changes via Regional Differencing for 3D CT Report Generation

arXiv:2608.05615v1 Announce Type: new Abstract: Computed tomography (CT) is widely used for clinical diagnosis and longitudinal follow-up, yet automatically generating accurate and complete radiology

tutorialsarxiv-cs-cv

Safety

ARGUS: Aligning Robot Scene Geometry Under Shifting Views with Large 3D Vision Models

arXiv:2608.05579v1 Announce Type: new Abstract: Large-scale visuomotor policies have demonstrated impressive performance across a wide range of robot manipulation tasks. However, despite this success,

safetyarxiv-cs-ro

Controllable Clothing: Precise Labels and Generation for Virtual Try-On with Latent Diffusion Models

arXiv:2608.05834v1 Announce Type: new Abstract: In this technical report, I present a new method for guiding image generation in the context of Virtual- Try-On (VITON). The proposed method leverages n

researcharxiv-cs-cv

Counterfactual Analysis via Large Language Models

arXiv:2608.05367v1 Announce Type: new Abstract: Counterfactual analysis aims to predict potential outcomes under hypothetical scenarios, offering valuable insights for decision-making. This paper inve

Echo Dot 2 can run 28M LLM at decent speed

model-releasesr-localllama

Code and instructions available here: https://github.com/albertoZurini/echo-dot-2-playground Hello there! After a few days of experimenting I was able to get a completely local voice pipeline running

HyTBE: Hyperbolic Target-Background Expert Model for Cross-Domain Infrared Small Target Detection

arXiv:2608.05771v1 Announce Type: cross Abstract: Infrared small target detection (IRSTD) has achieved substantial progress under domain-consistent evaluation, yet detector performance often degrades

Safety

Large Language Models Threaten Double-blind Review

arXiv:2608.05157v1 Announce Type: cross Abstract: Double blind peer review serves as the scientific community primary defense against status and affiliation bias. Its effectiveness rests on the assump

safetyarxiv-cs-ai

Tutorials

RxnCLF: Contrastive Transformation-Aware Reaction Foundation Model for Improved Reactivity Prediction

arXiv:2608.06259v1 Announce Type: new Abstract: Reaction yield prediction remains challenging because labeled data are scarce and reaction space is both combinatorially large and sparsely populated, l

tutorialsarxiv-cs-lg

ViSR-KGC: Visual Subgraph Reasoning with Vision-Language Models for Multimodal Knowledge Graph Completion

arXiv:2608.05833v1 Announce Type: new Abstract: Knowledge graph completion (KGC) aims to infer missing entities or relations from incomplete graph structures, and has evolved into multimodal knowledge

Tutorials

VLAff: Vision-Language-Affordance Model for Unified Actionable Affordances

arXiv:2608.05215v1 Announce Type: cross Abstract: Learning manipulation skills from human videos is promising for scalable robot learning. However, the embodiment mismatch between humans and robots ma

tutorialsarxiv-cs-cv

When Drafts Evolve: Speculative Decoding Meets Online Learning

arXiv:2603.12617v2 Announce Type: replace-cross Abstract: Speculative decoding has emerged as a widely adopted paradigm for accelerating large language model inference, where a lightweight draft model

Applications

Benchmarking Deep Learning Models for Dense Event Classification of Offshore Wind Infrastructure in Sentinel-1 Time Series

arXiv:2608.04706v1 Announce Type: new Abstract: Monitoring of offshore wind energy infrastructure life cycles, especially during the deployment phase, is an important contribution for stakeholders to

applicationsarxiv-cs-lg

Chain-of-Thought Monitoring Can Be Unreliable in Implicit-Influence Settings

arXiv:2608.04735v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring is increasingly treated as an important safety layer for frontier reasoning models. Most monitorability evaluations st

CSGen: A Multi-Domain Curvilinear Structure Generation Model via Hierarchical Multimodal Diffusion

arXiv:2608.04655v1 Announce Type: cross Abstract: Curvilinear structure analysis is an important and fundamental task in multimedia. However, the controllable generation of images with precise curvili

DelusionEval: Measuring Delusion-Linked Behaviors in AI Chatbots

arXiv:2608.05004v1 Announce Type: new Abstract: Mental health professionals have raised concerns about risks of psychological harm from interaction with large language models (LLMs), including 'delusi

Do Language Models Know Their Slang? Queer Slang Understanding in User-Generated Content

arXiv:2608.04847v1 Announce Type: new Abstract: Despite its cultural relevance and diffusion, queer slang remains underrepresented in Natural Language Processing research. Towards addressing this gap,

researcharxiv-cs-cl

Easy to Complete, Hard to Choose: Investigating LLM Performance on the ProverbIT Benchmark

arXiv:2608.04670v1 Announce Type: cross Abstract: Large Language Models (LLMs) have transformed computational linguistics and achieved remarkable performance across numerous natural language processin

Agents

Embedding Large Language Models into Flow Controls: An Agentic Framework for Adaptive and Trustworthy Automated Cooking

arXiv:2608.04768v1 Announce Type: new Abstract: Automated cooking robots have traditionally relied on predefined procedures and rule-based control, ensuring stable execution but offering limited perso

agentsarxiv-cs-cv

GEB-Bench: Abstract Structures Told in Many Voices

arXiv:2608.04111v1 Announce Type: cross Abstract: Can a model look at a river delta and a lightning bolt and see that they share a structure? We introduce GEB-Bench, a benchmark whose unit is an abstr

Group-Equivariant Diffusion Models for Lattice Field Theory

arXiv:2510.26081v2 Announce Type: replace-cross Abstract: Near the critical point, Markov Chain Monte Carlo (MCMC) simulations of lattice quantum field theories (LQFT) become increasingly inefficient

MathDebugger: Detecting and Diagnosing Errors in Synthetic Mathematical Data

arXiv:2502.19058v2 Announce Type: replace Abstract: Synthetic mathematical data has become an important resource for scaling the reasoning capabilities of large language models, yet errors in generate

Scrouting: Cost-Aware Routing of Coding Agents by Scouting the Repository First

arXiv:2608.04804v1 Announce Type: cross Abstract: Frontier language models can resolve repository-level software issues, but each attempt is expensive, and existing routers select a model from the iss

Agents

Spoken Function Calling: A New Perspective on Spoken Language Understanding for Large Audio Language Models

arXiv:2608.05126v1 Announce Type: new Abstract: Spoken Language Understanding (SLU) is the core component of task-oriented dialogue systems and a pivotal link in achieving seamless human-agent interac

agentsarxiv-cs-cl

The Calibration Floor: Format Repair Can Masquerade as Self-Correction at Small-to-Mid Scale

arXiv:2608.04355v1 Announce Type: new Abstract: Accuracy changes after language-model self-revision are usually interpreted as changes in reasoning. We show this can fail at the answer-extraction boun

A Unified 2D Framework for DeepLesion Detection, Segmentation and Short Report Generation

arXiv:2608.02805v1 Announce Type: cross Abstract: In previous work, we integrated large language models (LLMs) into the lesion segmentation model based on the ULS23 DeepLesion dataset, using short-for

Calibrating Semantic Uncertainty from Observable Language-Model Probabilities

arXiv:2607.17447v2 Announce Type: replace-cross Abstract: As generative artificial intelligence enters scientific and professional work, its uncertainty must be defined on the states that matter for i

researcharxiv-cs-cl

Conditionally Identifiable Latent-Environment Modeling for Out-of-Distribution Recommendation

arXiv:2608.03647v1 Announce Type: cross Abstract: Out-of-distribution (OOD) recommendation is vulnerable to preference shifts induced by a latent environment. Existing methods can infer latent states

Does Forgetting Transfer Across Modalities? A Real-World Benchmark for Cross-Modal Knowledge Unlearning Evaluation

arXiv:2608.03791v1 Announce Type: new Abstract: Vision-Language Models (VLMs), like Large Language Models (LLMs), may memorize sensitive, copyrighted, or harmful knowledge from their pretraining corpo

Efficient Multilingual Neural Machine Translation via Corpus-Driven Vocabulary Pruning: An English-Arabic Case Study

arXiv:2608.03480v1 Announce Type: new Abstract: The adoption of large pre-trained multilingual models for neural machine translation (MNMT) faces a major challenge: excessive memory and computational

Evaluating LLM Trade-offs for Enterprise Automation: Lessons from Workflow Generation in a Production Enterprise Platform

arXiv:2608.03311v1 Announce Type: cross Abstract: Enterprise compliance management requires rapid adaptation to evolving regulatory frameworks (e.g., DORA, AI RMF, FedRAMP) and tight remediation SLAs.

GPTKB 2.0: Direct Construction of Disambiguated Knowledge Bases from Large Language Models

arXiv:2608.03729v1 Announce Type: cross Abstract: Automated Knowledge Base Construction (AKBC) is a core NLP task, and recent work proposes generating knowledge bases directly from large language mode

GraphCliff: Short-Long Range Gating for Modeling Critical Activity Changes Caused by Subtle Molecular Differences

arXiv:2511.03170v3 Announce Type: replace-cross Abstract: The quantitative structure-activity relationship assumes a smooth mapping between molecular structure and biological activity. However, activi

I remember a time when 'flash' meant 32B

model-releasesr-localllama

I mean, Deepseek V4 Flash is an absolutely fantastic model, even though I can't run it on my machine it's so fascinating to see how it performs. Knowing that potentially it could be run at home is rea

Muon Meets Mamba: Spectral Optimization for State Space Models

arXiv:2608.03941v1 Announce Type: new Abstract: Muon is a recent optimizer that orthogonalizes the update to each weight matrix with a Newton-Schulz iteration, which performs steepest descent under th

ParVL: Parallel Scaling and Expandable Compute Allocation for Multimodal LLMs

arXiv:2608.04010v1 Announce Type: cross Abstract: Existing scaling strategies for Multimodal Large Language Models (MLLMs) typically expand either model parameters or sequential inference computation,

pi-Attention: Online Efficient Sparse Transformers for Long-Context Modeling

arXiv:2511.10696v3 Announce Type: replace-cross Abstract: Sparse attention is crucial in long-context Transformers, which restricts each token to a limited neighborhood and thereby reduces the quadrat

Risky Business: Measuring The Faithfulness-Safety Tension

arXiv:2608.03745v1 Announce Type: new Abstract: Chain-of-Thought (CoT) reasoning offers a promising window into model monitoring. However, monitoring relies on faithfulness, i.e., the model output str

Applications

To Describe or Construct Statistical Learning Models Using the Category-theoretical Language

arXiv:2608.03706v1 Announce Type: new Abstract: Statistical learning is a fascinating field that has long been the mainstream of machine learning/artificial intelligence. A large number of results hav

applicationsarxiv-cs-lg

UniPASE: A Generative Model for Universal Speech Enhancement with High Fidelity and Low Hallucinations

arXiv:2604.14606v2 Announce Type: cross Abstract: Universal speech enhancement (USE) aims to restore speech signals from diverse distortions across multiple sampling rates. We propose UniPASE, an exte

A reproducible and extensible framework for benchmarking competing risks survival models

arXiv:2608.00271v1 Announce Type: cross Abstract: A wide range of statistical and machine learning methods have been proposed for survival analysis with competing risks, where the occurrence of one ev

A Semiparametric Discrete Hawkes Model with a Collapsed Gaussian-Process Prior

arXiv:2509.21996v3 Announce Type: replace-cross Abstract: Hawkes processes are used in settings where past events increase the likelihood of future events occurring, resulting in a natural clustering

AOSpec: Action and Observation Co-Speculation for Low-Latency Agent Serving

model-releasesarxiv-cs-lg

arXiv:2608.00881v1 Announce Type: new Abstract: Large language model agents increasingly act through stateful tools, yet model generation and environment execution remain serialized at every step. As

Bagpiper: Solving Open-Ended Audio Tasks via Rich Captions

arXiv:2602.05220v4 Announce Type: replace Abstract: Current audio foundation models typically rely on rigid, task-specific supervision (e.g., speech recognition), addressing isolated factors of audio

Crushing the Evidence: A Dual-Penalty Evasion Framework for Fooling White-Box Explainable AI Auditors

model-releasesarxiv-cs-lg

arXiv:2608.00566v1 Announce Type: new Abstract: Post-hoc model explainers such as LIME, SHAP, and Integrated Gradients are widely deployed to audit models in high-stakes sensitive domains, including f