Search: “models”

Compete Then Collaborate: Frontier AI Teachers Build a Verifiable Curriculum to Improve a Coding Student Beyond Imitation

arXiv:2607.08255v1 Announce Type: new Abstract: Large language models increasingly serve as teachers generating training data for smaller students. Prior multi-teacher knowledge distillation methods m

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Curriculum Learning for Efficient Chain-of-Thought Distillation via Structure-Aware Masking and GRPO

DGX agent

arXiv:2602.17686v4 Announce Type: replace-cross Abstract: Distilling Chain-of-Thought (CoT) reasoning from large language models into compact student models presents a fundamental challenge: teacher r

safetyarxiv-cs-ai

10 Jul 2026

False Confidence: Automated Labels Confound Fairness Audits in Cervical Spine Segmentation

arXiv:2607.07852v1 Announce Type: cross Abstract: Automated segmentation of cervical-spine MRI is increasingly used in clinical workflows, yet no fairness audit exists for this anatomy. We show that a

Hallucination Self-Play: Bootstrapping Reinforced Detector via Evolved Generator

model-releasesarxiv-cs-cl

arXiv:2607.07993v1 Announce Type: new Abstract: Identifying faithfulness hallucinations in LLM-generated outputs remains challenging due to the scarcity of high-quality annotated data. Recent work rel

HumanForge: A Human-Centric Deepfake Video Benchmark with Multi-Agent Forgery Rationales

arXiv:2607.08705v1 Announce Type: new Abstract: Rapid advancements in video diffusion models and temporal editing tools have enabled the generation of highly realistic human-centric videos, posing unp

IMProofBench: Benchmarking AI on Research-Level Mathematical Proof Generation

model-releasesarxiv-cs-cl

arXiv:2509.26076v2 Announce Type: replace Abstract: As the mathematical capabilities of large language models (LLMs) improve, it becomes increasingly important to evaluate their performance on researc

LightCrafter: PBR-Conditioned Video Diffusion Refinement for Controllable and Consistent Relighting

arXiv:2607.08016v1 Announce Type: new Abstract: Video relighting requires balancing long-form temporal consistency with a physically grounded understanding of light transport, which depends on accurat

LiST: Lipschitz Scaling Training for Robust and Calibrated Neural Networks

arXiv:2607.07745v1 Announce Type: new Abstract: While accuracy, robustness, and calibration are all essential for reliable neural networks, they are often studied separately; developing models that sa

LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows

arXiv:2604.05182v2 Announce Type: replace-cross Abstract: We introduce the Large Sparse Reconstruction Model to study how scaling transformer context windows affects feed-forward 3D reconstruction. Al

Multi-Resolution Feature Stem for Diabetic Retinopathy lesion segmentation

arXiv:2607.08679v1 Announce Type: new Abstract: Diabetic Retinopathy (DR) is a leading cause of preventable blindness worldwide, requiring automated lesion segmentation using deep learning models for

Okay, this is winning big time for me right now. Surprised how good GPT-5.6 is at verifiying/advising and all high-level orchestrator capabi…

This post discusses positive experiences with GPT-5.6's capabilities in verification, advisory functions, and high-level orchestration tasks, suggesting the model performs better than expected in thes

model-releasesdair-ai--x

OmniFood-Bench: Evaluating VLMs for Nutrient Reasoning and Personalized Health Advice

arXiv:2607.08423v1 Announce Type: new Abstract: The rapid integration of Large Vision-Language Models (VLMs) into critical infrastructure promises to revolutionize personalized healthcare and dietary

Research

OpenCoF: Learning to Reason Through Video Generation

arXiv:2607.08763v1 Announce Type: cross Abstract: Reasoning has become a core capability for large models, especially when reliable decisions require understanding logical consequences. Recent video g

researcharxiv-cs-ai

ParamMute: Suppressing Knowledge-Critical FFNs for Faithful Retrieval-Augmented Generation

arXiv:2502.15543v4 Announce Type: replace-cross Abstract: Large language models (LLMs) integrated with retrieval-augmented generation (RAG) have improved factuality by grounding outputs in external ev

Persuasion Attacks Can Decrease Effectiveness of CoT Monitoring

arXiv:2607.08066v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring is a promising safety mechanism for AI agents, based on the premise that visible reasoning traces can surface misalign

ReCoLoRA: Spectrum-Aware Recursive Consolidation for Continual LLM Fine-Tuning

arXiv:2607.07719v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning adapts a large language model to one task cheaply, but across a task sequence LoRA-style methods keep stacking low-ran

Agents

Swapping Faces, Saving Features: A Dual-Purpose Pipeline for Pedestrian Privacy in ITS

arXiv:2607.08402v1 Announce Type: cross Abstract: Large-scale and diverse datasets are needed to train AI models to take real-time decisions for autonomous vehicles (AVs), an intelligent transportatio

agentsarxiv-cs-ai

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Two Axes of LLM Abstention: Answer Correctness and Question Answerability

arXiv:2607.08456v1 Announce Type: cross Abstract: A model should refuse two different things: answers it would get wrong, and questions it should not answer at all, such as unanswerable ones or ones r

safetyarxiv-cs-ai

Uncertainty-gated selection for block-sparse attention

model-releasesarxiv-cs-cl

arXiv:2607.07724v1 Announce Type: cross Abstract: Block-sparse attention scales long-context language models by replacing the O(N^2) softmax with a per-query top-k selection over key blocks. This cuto

Tutorials

VectorizationLLM: Smart Vectorization Based AI Assistant

arXiv:2607.07846v1 Announce Type: new Abstract: VectorizationLLM is a specialized Large Language Model based on Google open-weight LLMs. The model is designed to assist students to learn smart vectori

tutorialsarxiv-cs-ai

CompDiff: Hierarchical Compositional Diffusion for Fair and Zero-Shot Intersectional Medical Image Generation

arXiv:2603.16551v2 Announce Type: replace-cross Abstract: Generative models are increasingly used to augment medical imaging datasets for fairer AI, yet a key assumption often goes unexamined: that ge

Congrats to our llama cousins 🫡🦙

model-releasesjerry-liu--x

Congrats to our llama cousins 🫡🦙 Big day for Ollama! When we started, open models and the open source AI ecosystem were in their early days with few believers. Our belief in open source has never wave

HAJJv2-CrowdCount: Zero-Shot Benchmark for Dense Crowd Counting

arXiv:2607.07322v1 Announce Type: cross Abstract: Automated crowd counting in Hajj video is difficult not because current models lack capacity, but because the footage violates the assumptions those m

Optimization-Embedded Active Multi-Fidelity Surrogate Learning for Multi-Condition Airfoil Shape Optimization

arXiv:2603.17057v2 Announce Type: replace-cross Abstract: Active multi-fidelity surrogate modeling is developed for multi-condition airfoil shape optimization to reduce high-fidelity CFD cost while re

Agents

Physics-Audited Agentic Discovery in Scientific Machine Learning

arXiv:2607.07379v1 Announce Type: new Abstract: In agentic scientific machine learning (SciML), large language model (LLM) agents can discover surrogate models and select one by an automated score, ty

agentsarxiv-cs-ai

Agents

Power and Limitations of Aggregation in Compound AI Systems

arXiv:2602.21556v2 Announce Type: replace Abstract: When designing compound AI systems, a common approach is to query multiple copies of the same model and aggregate the responses to produce a synthes

agentsarxiv-cs-ai

Reinforcement Federated Learning Method Based on Adaptive OPTICS Clustering

arXiv:2306.12859v3 Announce Type: replace Abstract: Federated learning is a distributed machine learning technology, which realizes the balance between data privacy protection and data sharing computi

Specification Grounding Drives Test Effectiveness for LLM Code

arXiv:2607.06636v1 Announce Type: cross Abstract: Large language models frequently generate code that appears correct on typical inputs yet fails on edge cases, invalid inputs, and other specification

Safety

The Power of Backdoor Absorption in Community Training

arXiv:2607.06643v1 Announce Type: cross Abstract: Backdoor attacks severely threaten large-scale AI models. When model owners delegate training to external compute providers within a decentralized tra

safetyarxiv-cs-lg

TimEE: End-to-end Time Series Classification via In-Context Learning

arXiv:2607.07500v1 Announce Type: cross Abstract: Time series classification (TSC) is dominated by a two-stage paradigm: train a feature encoder -- either from scratch on the target dataset or via pre

TRACE-Seg3D: Counterfactual Context Auditing For Robust 3D Glioma Segmentation Under Institutional Shift

arXiv:2607.07038v1 Announce Type: new Abstract: Medical image segmentation models can achieve strong benchmark performance while remaining sensitive to scanner, protocol, and institutional variation.

Tree-of-Thoughts Reasoning for Text-to-Image In-Context Learning

arXiv:2607.07117v1 Announce Type: cross Abstract: In text-to-image in-context learning (T2I-ICL), a model has to infer a latent compositional pattern from fewshot demonstrations for generating a query

Try @Grok 4.5!

model-releaseselon-musk--x

Try @Grok 4.5! Grok 4.5 is the top non-Anthropic model on AA-Briefcase, combining frontier agentic knowledge work capabilities with leading cost and time-efficiency Yesterday @SpaceXAI released Grok 4

Unraveling Machine Behavior by Multi-Level Bias Analysis and Detection: Methodology and Application to Computer Vision

arXiv:2607.07236v1 Announce Type: new Abstract: This study investigates the presence and propagation of bias within Neural Networks through a comprehensive multi-level analysis spanning the learned la

We comprehensively benchmarked GPT-5.6 on document understanding. At a high-level there's no change between GPT-5.6 Sol and GPT-5.5 in terms…

model-releasesjerry-liu--x

We comprehensively benchmarked GPT-5.6 on document understanding. At a high-level there's no change between GPT-5.6 Sol and GPT-5.5 in terms of performance over tables, text, charts, layout, and more.

Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation

arXiv:2607.05985v1 Announce Type: new Abstract: This paper presents a black-box evaluation framework to systematically assess the ability of Large Language Models (LLMs) to generate Design Structure M

Benchmarking the Robustness of Autonomous Driving to Environmental Illusions: A Lane Perception Perspective

arXiv:2607.05783v1 Announce Type: new Abstract: Environmental illusions (eg., shadows, reflections, and tire marks) are naturally existing yet overlooked phenomena in real-world driving environments.

Applications

CCBENCH: Assessing LLM Cultural Competence via Implicitly Signaled Norms using Health Queries

arXiv:2607.05405v1 Announce Type: cross Abstract: To interact with users fairly and without stereotyping, AI models must display cultural competency, i.e., the ability to infer and adapt to a user's i

applicationsarxiv-cs-ai

Correct

model-releaseselon-musk--x

Correct Grok 4.5 goes public tomorrow. Here’s everything that’s known. The model runs on V9, xAI’s new 1.5 trillion parameter foundation, roughly three times the size of the v8-small architecture behi

Doomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade

arXiv:2607.06503v1 Announce Type: new Abstract: Large language model (LLM) agents solving multi-step tasks frequently commit to trajectories that are doomed to fail, yet continue to consume substantia

Gemini Enterprise for Education named a Commander in Tambellini StarChart™: 2026 AI Agents for Administrative Efficiency—Agent Platforms

model-releasesgoogle-cloud-ai

The agentic AI era is here, transforming how higher education institutions innovate, operate, and fundamentally empower learners, faculty, and researchers. AI agents can deliver unprecedented efficien

Safety

MAME: Multidimensional Adaptive Metamer Exploration with Human Perceptual Feedback

arXiv:2503.13212v3 Announce Type: replace Abstract: Alignment between human brain networks and artificial models has become an active research area in vision science and machine learning. A widely ado

safetyarxiv-cs-lg

Local Ai

Measuring the practice of shared-decision making (OPTION12): An Investigation into Open-sourced Smaller LLMs (OS-sLLMs) for Better Privacy and Sustainability

arXiv:2607.06127v1 Announce Type: new Abstract: We present LLM4SDM, the first study of open-source smaller language models (OS-sLLMs) for automated assessment of shared decision making (SDM) using the

local-aiarxiv-cs-cl

MobileWan: Closing the Quality Gap for Mobile Video Diffusion

arXiv:2607.06173v1 Announce Type: new Abstract: Recent advances in video diffusion have been driven by scaling transformer-based architectures to billions of parameters, substantially improving visual

More Convincing, Not More Correct: Self-Play Reward Hacking of Reference-Free LLM Judges

arXiv:2607.05904v1 Announce Type: new Abstract: Training a language model against its own reference-free judgments (the premise of self-rewarding, self-play, and LLM-as-a-judge pipelines) assumes a mo

Multi-Task Instruction Tuning via Data Scheduling for Low-Resource Arabic SpeechLLMs

arXiv:2601.12494v3 Announce Type: replace-cross Abstract: Audio large language models (LLMs) enable unified speech understanding and generation, but adapting them to linguistically complex and dialect

NVIDIA Nemotron Achieves Benchmark-Leading Performance With LangChain Deep Agents Harness

model-releasesnvidia-blog

NVIDIA Nemotron 3 Ultra is offering leading performance at lower cost than top closed models with the largest and most widely adopted AI agent orchestration platform. LangChain tuned its Deep Agents h

PatchOptic for Shared-State LLM Workflows with Projected Views and Verified Structured Updates

arXiv:2607.05483v1 Announce Type: cross Abstract: Agentic workflows often operate over shared, structured state. Because LLM context windows are limited, each model invocation is typically shown only