Search: “models”

Select-to-Act: Hierarchical Reinforcement Learning via Adaptive Language Guidance

arXiv:2606.22350v1 Announce Type: new Abstract: Reinforcement Learning (RL) has been widely applied to sequential decision-making, yet it often suffers from poor sample efficiency due to costly intera

Agents

Semantic Browsing: Controllable Diversity for Image Generation

DGX agent

arXiv:2606.23679v1 Announce Type: new Abstract: Modern text-to-image models excel in visual fidelity and prompt adherence. However, this strict adherence comes at the cost of diversity: generated samp

agentsarxiv-cs-cv

23 Jun 2026

Temporal Causal Prior-Data Fitted Networks for Panel Data with Learned Reliability Signals

arXiv:2606.20889v1 Announce Type: new Abstract: Estimating causal effects in industrial time series requires handling temporal dynamics, time-varying treatments, and unobserved confounders. Existing c

The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction

model-releasesarxiv-cs-cv

arXiv:2603.01250v3 Announce Type: replace Abstract: Breast cancer is the most frequently diagnosed malignancy among women worldwide and a leading cause of cancer-related mortality. Dynamic contrast-en

The Metanym Game: A Self-Contained, Self-Consistent LLM Peer-Community Benchmark for Structural Intelligence

arXiv:2606.21008v1 Announce Type: cross Abstract: The metanym game is a competitive word game for LLMs that measures structural intelligence against established cognitive-science constructs. No conten

サカナAIが新サービス「フグ」、複数AI束ねプログラミングで高性能 https://www.nikkei.com/article/DGXZQOUC2265B0S6A620C2000000/?n_cid=SNSTW001&n_tw=1782121582

Sakana AI announced a new service called 'Fugu' that bundles multiple AI models together through programming to achieve higher performance capabilities. The approach combines various AI systems in a c

researchdavid-ha--x

Local Ai

b9761

local-aillama-cpp-releases

The b9761 release of llama.cpp includes server improvements with model downloading moved to a dedicated process and real-time model load progress tracking via /models/sse endpoint. The release feature

Agents

OMG! Fugu Ultra is ridiculously good at these 3D renders.

OMG! Fugu Ultra is ridiculously good at these 3D renders. Media Introducing Sakana Fugu: A full multi-agent orchestration system accessible via a single model API. Our ‘Fugu Ultra’ model matches the p

agentsdair-ai--x

Industry

the number of providers for glm 5.2 is insane. i count 20 of them.

GLM 5.2, likely Alibaba's language model, has achieved significant provider adoption with approximately 20 different providers offering access to the model. This suggests widespread integration and av

industryclem-delangue--x

We’re also launching the OpenAI Daybreak Cyber Partner Program with leading security software and services providers. Participating partners…

We’re also launching the OpenAI Daybreak Cyber Partner Program with leading security software and services providers. Participating partners can use GPT‑5.5 with Trusted Access for Cyber in the securi

model-releasesopenai--x

We’re expanding OpenAI Daybreak to help democratize patching vulnerable software at machine speed: - Codex Security plugin: find, validate, …

We’re expanding OpenAI Daybreak to help democratize patching vulnerable software at machine speed: - Codex Security plugin: find, validate, and fix vulnerabilities right inside Codex - The full versio

model-releasesopenai--x

Local Ai

glm 5.2 is awesome

GLM 5.2 is a language model released or discussed on X (formerly Twitter) via Ollama, a platform for running large language models locally. The post expresses positive sentiment about GLM 5.2's capabi

local-aiollama--x

20 Jun 2026

Local Ai

GLM 5.2 is really good. Wow.

GLM 5.2 is a language model available through Ollama that has received positive user feedback for its performance capabilities. The post appears to be a social media testimonial praising the model's q

local-aiollama--x

20 Jun 2026

A Physics-Inspired Optimizer: Velocity Regularized Adam

arXiv:2505.13196v3 Announce Type: replace-cross Abstract: We introduce Velocity-Regularized Adam (VRAdam), a physics-inspired optimizer for training deep neural networks that draws on ideas from quart

A PubMed-Scale Dataset of Structured Biomedical Abstracts

arXiv:2606.11361v1 Announce Type: cross Abstract: Structured abstracts are important for biomedical literature processing, by facilitating information retrieval, text mining, and knowledge synthesis.

AI Coding Agents in Social Science: Methodologically Diverse, Empirically Consistent, Interpretively Vulnerable

arXiv:2606.11456v1 Announce Type: cross Abstract: The deployment of LLM-based agents in scientific analysis raises opposing concerns: that agents may reduce methodological diversity, or that they may

An Electric Potential-Augmented Benchmark Dataset for Physics-Guided Image Reconstruction of Electrical Capacitance Tomography

model-releasesarxiv-cs-cv

arXiv:2606.12226v1 Announce Type: new Abstract: While deep learning has significantly advanced image reconstruction of Electrical Capacitance Tomography (ECT), most data-driven methods map directly be

APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies

arXiv:2606.12366v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models that couple pretrained Vision-Language Models (VLMs) with continuous action experts have achieved strong manipulatio

safetyarxiv-cs-ro

Atlas H&E-TME: Scalable AI-Based Tissue Profiling at Expert Pathologist-Level Accuracy

arXiv:2606.12346v1 Announce Type: cross Abstract: Hematoxylin and eosin (H&E) staining is the cornerstone of histopathology, yet scalable, quantitative analysis of H&E whole-slide images (WSIs) remain

Tutorials

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching

arXiv:2606.11583v1 Announce Type: new Abstract: Text-attributed graphs (TAGs) underlie real-world applications such as citation networks, social media, and e-commerce. Few-shot graph learning on TAGs

tutorialsarxiv-cs-lg

Bridging the sim2real gap in the table tennis robot with a transformer-based ball states predictor

model-releasesarxiv-cs-ro

arXiv:2606.11464v1 Announce Type: new Abstract: Robotic table tennis is a representative benchmark for high-speed, closed-loop robotic control in dynamic environments, where accurate and fast predicti

Can AI Agents Synthesize Scientific Conclusions?

arXiv:2606.11337v1 Announce Type: new Abstract: Scientific AI agents increasingly retrieve evidence, reason across sources, and synthesize conclusions used in consequential decisions. Yet, their abili

Can News Predict the Market? Limits of Zero-Shot Financial NLP and the Role of Explainable AI

arXiv:2606.12210v1 Announce Type: new Abstract: Can financial news reliably predict short-term stock movements? Despite advances in large language models, this question remains unresolved. We revisit

researcharxiv-cs-cl

Applications

Categorical Robustness Assessment for Machine Learning based Network Intrusion Detection Systems

arXiv:2606.12075v1 Announce Type: cross Abstract: Network Intrusion Detection Systems (NIDS) heavily utlize Machine Learning (ML) but ML models can be manipulated via adversarial attacks. These attack

applicationsarxiv-cs-lg

Certifiable Safe RLHF: Semantic Grounding and Fixed Penalty Constraint Optimization for Safer LLM Alignment

arXiv:2510.03520v2 Announce Type: replace-cross Abstract: Ensuring safety is a foundational requirement for large language models (LLMs). Achieving an appropriate balance between enhancing the utility

safetyarxiv-cs-ai

Context-Aware Multimodal Claim Verification in Spoken Dialogues

arXiv:2606.11420v1 Announce Type: new Abstract: Every day, millions absorb claims from podcasts and streams that no fact-checker ever sees. Spoken misinformation is built through conversation, where c

Debiasing Without Protected Attributes: Latent Concept Erasure from Textual Profiles

arXiv:2606.12088v1 Announce Type: new Abstract: Most fairness research in NLP assumes direct access to protected attributes such as gender, race, or nationality. In practice, however, such information

DeMix: Debugging Training Data with Mixed Data Error Types by Investigating Influence Vectors

arXiv:2606.11616v1 Announce Type: new Abstract: High-quality training data is essential for the success of machine learning models. However, real-world datasets often contain mixed types of errors ari

safetyarxiv-cs-lg

Applications

DIRECT: When and Where Should You Allocate Test-Time Compute in Embodied Planners?

arXiv:2606.12402v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as high-level planners for embodied agents, with an emerging strategy of scaling test-time com

applicationsarxiv-cs-ai

Tutorials

FOCUS: DLLMs Know How to Tame Their Compute Bound

arXiv:2601.23278v2 Announce Type: replace-cross Abstract: Diffusion Large Language Models (DLLMs) offer a compelling alternative to Auto-Regressive models, but their deployment is constrained by high

tutorialsarxiv-cs-cl

GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs

arXiv:2606.11898v1 Announce Type: new Abstract: Research on Text-Attributed Graphs (TAGs) has gained significant attention recently due to its broad applications across various real-world data scenari

Human-Guided Agentic AI for Multimodal Clinical Prediction: Lessons from the AgentDS Healthcare Benchmark

arXiv:2602.19502v2 Announce Type: replace Abstract: Agentic AI systems are increasingly capable of autonomous data science workflows, yet clinical prediction tasks demand domain expertise that purely

Machine-learning clustering of close-in exoplanet populations: links to pebble accretion

arXiv:2606.11737v1 Announce Type: cross Abstract: Close-in exoplanets exhibit a wide range of orbital architectures and physical properties shaped by both formation conditions and migration processes.

Mind the Perspective: Let's Reason Recursively for Theory of Mind

arXiv:2606.11724v1 Announce Type: new Abstract: Theory of Mind (ToM) reasoning requires inferring agents' beliefs from partial and asymmetric observations, which remains an open challenge for LLMs. Ex

MSUE: Multi-Modal Soccer Understanding Expert

arXiv:2606.12106v1 Announce Type: cross Abstract: This paper presents our solution to the 2026 SoccerNet VQA Challenge. We first develop a cost-effective data synthesis pipeline driven by a Vision-Lan

Multi-Rate Mixture of Experts for Accelerating Liquid Neural Network Training

arXiv:2606.12240v1 Announce Type: cross Abstract: Multivariate time-series data often exhibit complex temporal dependencies, irregular sampling, and heterogeneous dynamics across multiple time scales,

researcharxiv-cs-ai

Multi-View In-Cabin Monitoring System for Public Transport Vehicles

arXiv:2606.11739v1 Announce Type: cross Abstract: We introduce a multi-view in-cabin monitoring dataset for public transportation with synchronized RGB and depth images from four inward-facing cameras

NSVQ: Mitigating Codebook Collapse by Stabilizing Encoder Drift in Vector Quantization

arXiv:2606.11363v1 Announce Type: new Abstract: Vector quantization is central to modern generative modeling pipelines, but large-codebook VQ models often suffer from codebook collapse. We identify en

researcharxiv-cs-cv

OCSVM-Guided Representation Learning for Unsupervised Anomaly Detection

arXiv:2507.21164v2 Announce Type: replace-cross Abstract: Unsupervised anomaly detection (UAD) aims to detect anomalies without labeled data, a necessity in many machine learning applications where an

On the Limits of LLM-as-Judge for Scientific Novelty Assessment

arXiv:2606.12071v1 Announce Type: cross Abstract: LLMs are increasingly used to generate and judge scientific ideas. This makes novelty evaluation a central problem. Full idea evaluation is difficult

Open Materials Generation with Inference-Time Reinforcement Learning

arXiv:2602.00424v2 Announce Type: replace Abstract: Continuous-time generative models for crystalline materials enable inverse materials design by learning to predict stable crystal structures, but in

safetyarxiv-cs-lg

PCS-UQ: Uncertainty Quantification via the Predictability-Computability-Stability Framework

arXiv:2505.08784v2 Announce Type: replace-cross Abstract: As machine learning (ML) enters high-stakes domains, trustworthy uncertainty quantification (UQ) is essential for safety. In this paper we int

Tutorials

Position: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces!

arXiv:2504.09762v4 Announce Type: replace Abstract: Intermediate token generation (ITG), where a model produces output before the solution, has become a standard method to improve the performance of l

tutorialsarxiv-cs-ai

Projected random forests and conformal prediction of circular data

arXiv:2410.24145v3 Announce Type: replace-cross Abstract: We apply conformal prediction techniques to regression problems with circular responses, producing prediction sets with adaptive arc length an

researcharxiv-cs-lg

ReMoT: Reinforcement Learning with Motion Contrast Triplets

model-releasesarxiv-cs-cv

arXiv:2603.00461v3 Announce Type: replace Abstract: We present ReMoT, a unified training paradigm to systematically address the fundamental shortcomings of VLMs in spatio-temporal consistency -- a cri

The Long Tail, Not the Front Page: Cold-Start Prediction of Crowd Highlight Salience

arXiv:2606.11654v1 Announce Type: cross Abstract: A social highlighter's most useful signal -- which passages a crowd of readers marks -- exists only for documents people have already read. Can the ag

researcharxiv-cs-cl

The Structural Attention Tax: How Retrieval Format Hijacks In-Context Learning Independent of Content

arXiv:2606.11198v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) systems inject external knowledge to improve LLM outputs, yet the format of injected content -- distinct from its

Time-Conditioned and Multi-Time Survival Prediction from 2D PET/CT Projections in Lung Cancer

arXiv:2606.12140v1 Announce Type: new Abstract: Accurate prediction of overall survival (OS) from positron emission tomography/computed tomography (PET/CT) can support personalized treatment and follo

researcharxiv-cs-cv