Search: “reasoning”

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

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Model Releases

Is MoE Routing a Huffman Code? Discovering the Frequency-Diversity Law in Chain-of-Thought

DGX agent

arXiv:2607.20427v1 Announce Type: cross Abstract: Mixture-of-Experts architectures have revolutionized scaling, yet the underlying logic of their routing remains a black box. In this paper, we uncover

model-releasesarxiv-cs-ai

24 Jul 2026

Learn2Zinc: Fine-tuning Small Language Models for Text-to-Model Translation in MiniZinc

arXiv:2607.20456v1 Announce Type: cross Abstract: Large language models excel at code generation for mainstream programming languages but struggle with rare, domain-specific languages such as MiniZinc

Applications

Learning to Detect UI Principle Violations via Reinforcement Learning

arXiv:2607.20690v1 Announce Type: new Abstract: Small language models and coding agents increasingly generate web front-end code, yet their outputs are typically evaluated primarily for functional cor

applicationsarxiv-cs-cl

MagicMakeup: A Region-Controllable Diffusion Transformer for High-Fidelity Makeup-Transfer

arXiv:2607.20924v1 Announce Type: new Abstract: Makeup-transfer applies the reference makeup to the source face while preserving the source identity. Despite advances in full-face editing by diffusion

Moir: Let the Model Direct Its Own Story for Robust Cross-Domain Knowledge Editing

arXiv:2607.20433v1 Announce Type: cross Abstract: While language models remain frozen at their training state, the world evolves continuously. Knowledge editing has emerged as a key alternative to ful

MVEI & EmObserver: Empowering MLLM-Oriented Visual Emotional Intelligence via Emotion Statement Judgement

arXiv:2607.21061v1 Announce Type: new Abstract: Affective Image Content Analysis (AICA) aims to recognize and understand emotions elicited by visual content, representing an indispensable step toward

Hardware

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

arXiv:2607.20709v1 Announce Type: new Abstract: Traditional agent development is split across prompt templates, tool schemas, callback code, and workflow graphs. We present NVIDIA Object-Oriented Agen

hardwarearxiv-cs-ai

OPOD: On-Policy Omni Distillation

arXiv:2607.20918v1 Announce Type: new Abstract: Omni-modal models can handle text, images, and audio in one system, but improving all of these abilities together remains difficult. Training a single m

Tutorials

Probabilistic Physics-Aware Machine Learning Predictions of Electric Truck Energy Consumption with Field Data

arXiv:2607.19054v2 Announce Type: replace Abstract: In this work, we incorporate first principle physics into the construction of data-driven methods by considering a model that accounts for the diffe

tutorialsarxiv-cs-lg

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

Routing Without Training: Controllable-Ratio LLM Offloading via Reliability Gating

arXiv:2607.20481v1 Announce Type: new Abstract: Local-cloud collaboration is a practical way to deploy large language models under resource constraints, but existing methods often rely on trained rout

local-aiarxiv-cs-ai

Self-Evolving Recommendation System: End-To-End Autonomous Model Optimization With LLM Agents

arXiv:2602.10226v2 Announce Type: replace-cross Abstract: Optimizing large-scale machine learning systems, such as recommendation models for global video platforms, requires navigating a massive hyper

Skill-Contracted Agents for Evidence-Aware Materials Literature Analysis

arXiv:2607.20431v1 Announce Type: new Abstract: Materials science literature analysis requires simultaneous attention to composition, processing, characterization, and property relationships, yet conv

agentsarxiv-cs-cl

StabilityBench: Benchmarking Instability in LLMs

arXiv:2607.20558v1 Announce Type: cross Abstract: AI Assistants are increasingly deployed in high-stakes settings, such as healthcare or government services. Yet their real-world behavior remains poor

Telco-GAIA: Bilingual Benchmark for Agents in Telecom Domain

arXiv:2607.20510v1 Announce Type: new Abstract: We introduce Telco-GAIA, a bilingual, multi-modal benchmark for evaluating tool-using agents on the data of a real-world telecommunications operator. Te

Applications

The Boundaries of Automation: A Theory of Persistent Human Participation

arXiv:2607.21547v1 Announce Type: new Abstract: The rapid progress of AI has intensified the long-standing pursuit of automation: replacing human participation with algorithms wherever possible. Impli

applicationsarxiv-cs-ai

The Storyteller in the Model: Narrative Pattern Inheritance, Escalation Dynamics, and Alignment Governance in LLMs

arXiv:2607.20449v1 Announce Type: cross Abstract: LLMs are trained predominantly on human-authored text, yet the structural and narrative conventions embedded in that text are rarely examined as a sou

TransBiolab: A Real-World Multi-View Dataset of Cluttered Transparent Biomedical Objects

arXiv:2607.21071v1 Announce Type: new Abstract: Autonomous biomedical laboratories increasingly rely on visual perception to recognize, localize, and manipulate transparent plasticware, yet high-quali

Visual Contrastive Self-Distillation

arXiv:2607.21556v1 Announce Type: cross Abstract: On-policy self-distillation (OPSD) is promising as it removes the external teacher required by on-policy distillation (OPD), yet it still needs asymme

What I learned using Ollama on a real Paperless archive: model choice was not the main problem

I maintain Tagvico, an open-source companion for Paperless-ngx. I added Ollama because document text is exactly the kind of data many people do not want to send to a hosted model. The surprising failu

local-air-ollama

WhereEdit: Mask-aware Local Latent Editing for One-Step Image Editing

arXiv:2607.20883v1 Announce Type: new Abstract: Recent one-step text-to-image (T2I) models enable efficient image synthesis and provide new opportunities for real-time image editing. However, existing

Zagreus-0.4B-por a small open source language model for Portuguese

model-releasesr-localllama

mii-llm, an open source AI lab, released Zagreus-0.4B-por, a compact bilingual Portuguese–English language model pretrained entirely from scratch. The model has approximately 400 million parameters an

A local-first harness for multi-agent workflows

Hey all, I’ve been working on this in my spare time and finally feel ready to share it outside my own circles. Arbiter is a single binary for running agents locally. I originally built it because I wa

local-air-ollama

A Multi-Dimensional Evaluation of Explainability in Media Bias Detection

arXiv:2607.19954v1 Announce Type: new Abstract: Detecting media bias automatically is difficult because biased framing is often subtle, yet in domains such as news analysis, accurate predictions alone

safetyarxiv-cs-cl

Research

Adaptive Multi-Expert Graph Transformer for Interpretable EEG-Based Diagnostics

arXiv:2607.19429v1 Announce Type: new Abstract: Electroencephalographic (EEG) abnormalities arise from dynamic changes in neural synchrony across spatial and temporal scales, yet many computational ap

researcharxiv-cs-lg

Clinical Pathways as Safety Specifications for Physical AI in Hospital Wards

arXiv:2607.19827v1 Announce Type: new Abstract: Ensuring safety in Physical AI systems operating in real-world environments is a critical challenge, particularly in hospital wards where vulnerable pat

safetyarxiv-cs-ro

Co-Evolving LLM Evaluators and Policies via DynamicRubric

arXiv:2607.20083v1 Announce Type: cross Abstract: Post-training with evaluator feedback on policy-induced samples serves as a major mechanism for improving large language models. As policies improve,

Congestion-Aware Robot Tour Planning in Crowded Environments

arXiv:2606.19031v2 Announce Type: replace Abstract: Autonomous mobile service robots are often required to complete tours that require navigating through a set of locations in an environment. Example

agentsarxiv-cs-ro

Continual Video-MLLM Adaptation over Evolving Domains

arXiv:2607.18716v1 Announce Type: new Abstract: Video multimodal large language models have shown strong capability in video understanding, yet their adaptation to sequentially evolving domains remain

Contour Errors: Ego-Centric Matching for 3D Multi-Object Tracking Performance Evaluation

arXiv:2506.04122v4 Announce Type: replace Abstract: Open-loop performance evaluation of 3D multi-object tracking in autonomous driving requires matching criteria that effectively penalize translationa

safetyarxiv-cs-cv

CR-Refiner: An Object-Centric Optimal Transport Reranker for Edit-Conditioned 3D Scene Retrieval

arXiv:2607.19115v1 Announce Type: new Abstract: Edit-conditioned 3D scene retrieval pairs a reference 3D room with a natural-language modification and retrieves rooms from a corpus that satisfy the ed

D3VL: Understanding Driving Scenes from 3D Time Series Data and Video with Language Models

arXiv:2607.19528v1 Announce Type: cross Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have triggered the development of end-to-end MLLMs for autonomous driving. However, the ma

Did Alice Do Wrong? Cross-Cultural Differences in Student Perceptions of Generative AI Use in University Computing Education

arXiv:2607.19699v1 Announce Type: cross Abstract: The rise of generative AI (GenAI) in higher education has prompted urgent debates surrounding academic integrity and ethical use. This study examines

local-aiarxiv-cs-ai

FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense

arXiv:2607.19674v1 Announce Type: cross Abstract: Federated Graph Neural Networks (FedGNNs) are highly vulnerable to backdoor poisoning, yet existing defenses typically rely on rule-based approaches t

local-aiarxiv-cs-ai

Research

Fidelity Before Structure: Verbatim Chunks Beat Lossy Artifact Extraction in Long-Conversation LLM Memory

arXiv:2601.00821v4 Announce Type: replace Abstract: A growing class of conversational-memory systems compresses dialogue history into structured artifacts (extracted facts, decisions, or events) on th

researcharxiv-cs-ai

Harnessing Disagreement: Detecting Correlated Agreement Blindness in Multi-Agent Triage

arXiv:2607.19899v1 Announce Type: cross Abstract: Disagreement-triggered escalation can create a structural blind spot in multi-agent arbitration: as base learners improve, they tend to converge, weak

safetyarxiv-cs-lg

Knowledge-Centric Self-Improvement

arXiv:2607.19592v1 Announce Type: new Abstract: Self-improving AI systems typically treat the agent as the object that improves, by optimizing prompts, workflows, harnesses, or even the agent's own co

agentsarxiv-cs-ai

Laguna-S-2.1 'thinking forever' loops seem to be a quantization artifact

model-releasesr-localllama

If you're running Laguna S 2.1 on llama.cpp and hitting thinking loops because it won't close its </think> tags, you might want to look at your quant before you spend too much time tweaking settings.

Ling-3.0-flash, the new MoE model from @AntLingAGI, is now free in Nous Portal for the next week! At 124B parameters and 5.1B active, it's q…

Ling-3.0-flash, the new MoE model from @AntLingAGI, is now free in Nous Portal for the next week! At 124B parameters and 5.1B active, it's quick to run and built for agent workloads: coding, search, r

agentsnous-research--x

Mitigating Modality and Language-Style Gaps for Zero-Shot Video Moment Retrieval

arXiv:2607.19027v1 Announce Type: new Abstract: Zero-shot video moment retrieval aims to overcome the limitations of traditional approaches that require large-scale datasets annotated with text and it

safetyarxiv-cs-cv

No Training, Better Flights: Test-Time Scaled VLMs for UAV Navigation

arXiv:2607.19288v1 Announce Type: new Abstract: Test-time scaling offers a promising method to improve the inference performance of Vision-Language Models (VLMs) without additional training. Existing

safetyarxiv-cs-cv

Research

Notes to Self: Can LLMs Benefit from Experiential Abstractions?

arXiv:2607.20372v1 Announce Type: new Abstract: Humans distill experience into reusable abstractions, e.g., strategies and cautionary reminders, and apply them to gradually solve problems more effecti

researcharxiv-cs-cl

OPD-IAD: From Language Judgment to Industrial Anomaly Detection via On-Policy Self-Distillation

arXiv:2607.18850v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have recently shown strong potential for industrial anomaly detection (IAD) by providing image-level anomaly judgme

local-aiarxiv-cs-cv

Industry

OpenAI is making big claims as it rolls out ChatGPT Health to everyone

OpenAI is rolling out ChatGPT Health to everyone in the US on Thursday, allowing more people to connect their medical records and health-tracking information to the chatbot. During a briefing, Ashley

industrythe-verge-ai

OpenSkillRisk: Benchmarking Agent Safety When Using Real-World Risky Third-Party Skills

model-releasesarxiv-cs-cl

arXiv:2607.20121v1 Announce Type: new Abstract: LLM-based agents leverage third-party skills to extend their capabilities in open-world scenarios. However, third-party skills can introduce extra secur

Applications

Overview of FinMMEval 2026 Task 1: Multilingual Financial Multiple-Choice Question Answering

arXiv:2607.19856v1 Announce Type: cross Abstract: FinMMEval 2026 Task 1 evaluates multilingual financial multiple-choice question answering in English, Chinese, Arabic, and Hindi. The task tests wheth

applicationsarxiv-cs-ai

[Paper] SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD

model-releasesr-localllama

Full-parameter post-training of trillion-parameter-scale MoE models introduces substantial system-level challenges for large-scale distributed training, including severe memory pressure, non-overlappe