Search: “models”

World-Ego Modeling for Long-Horizon Evolution in Hybrid Embodied Tasks

arXiv:2605.19957v1 Announce Type: cross Abstract: World models are widely explored in embodied intelligence, yet they typically predict distinct evolutions of the world and the ego within a single str

20 May 2026

A Mechanistic Model for Collective Motion from Sensorimotor Regularities

DGX agent

arXiv:2605.16522v1 Announce Type: new Abstract: Collective behavior in animals has long been modeled through self-propelled particle models, which reproduce striking group-level phenomena through abst

agentsarxiv-cs-ro

19 May 2026

DevBench: A Realistic, Developer-Informed Benchmark for Code Generation Models

arXiv:2601.11895v3 Announce Type: replace-cross Abstract: DevBench is a telemetry-driven benchmark designed to evaluate Large Language Models (LLMs) on realistic code completion tasks. It includes 1,8

EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models

arXiv:2605.17070v1 Announce Type: new Abstract: While large vision-language models (VLMs) are increasingly adopted as the perceptual backbone for embodied agents, existing benchmarks often rely on que

GIM: Evaluating models via tasks that integrate multiple cognitive domains

arXiv:2605.18663v1 Announce Type: new Abstract: As LLM benchmarks saturate, the evaluation community has pursued two strategies to increase difficulty: escalating knowledge demands (GPQA, HLE) or remo

I remember when people were saying 'It's useless to open-source big models because nobody will be able to run them fast'....

model-releasesclem-delangue--x

I remember when people were saying 'It's useless to open-source big models because nobody will be able to run them fast'.... Cerebras is now running Kimi K2.6 – a trillion parameter model – in enterpr

Machine Unlearning for Masked Diffusion Language Models

arXiv:2605.18253v1 Announce Type: cross Abstract: Recent masked diffusion language models (MDLMs), such as LLaDA and Dream, have achieved performance comparable to autoregressive large language models

Prompt Compression in Diffusion Large Language Models: Evaluating LLMLingua-2 on LLaDA

arXiv:2605.17932v1 Announce Type: cross Abstract: Prompt compression reduces inference cost and context length in large language models, but prior evaluations focus primarily on autoregressive archite

ProxyKV: Cross-Model Proxy Pruning for Efficient Long-Context LLM Inference

arXiv:2605.16360v1 Announce Type: cross Abstract: Efficient long-context inference in Large Language Models (LLMs) is severely constrained by the Key-Value (KV) cache memory wall, yet existing pruning

Safety

Real-Time Aligned Reward Model beyond Semantics

arXiv:2601.22664v4 Announce Type: replace Abstract: Reinforcement Learning from Human Feedback (RLHF) is a pivotal technique for aligning large language models (LLMs) with human preferences, yet it is

safetyarxiv-cs-ai

Safety

Right Predictions, Misleading Explanations: On the Vulnerability of Vision-Language Model Explanations

arXiv:2605.16651v1 Announce Type: new Abstract: Explanation mechanisms are increasingly used to support transparency and trust in vision-language models (VLMs), particularly in settings where model de

safetyarxiv-cs-cv

SAFE-SVD: Sensitivity-Aware Fidelity-Enforcing SVD for Physics Foundation Models

arXiv:2605.17985v1 Announce Type: cross Abstract: We propose a new method for compressing physics foundation models (PFMs) which is a new trend in AI for Science. While model compression is essential

researcharxiv-cs-ai

Vision Inference Former: Sustaining Visual Consistency in Multimodal Large Language Models

arXiv:2605.18160v1 Announce Type: cross Abstract: In recent years, multimodal large language models (MLLMs) have achieved remarkable progress, primarily attributed to effective paradigms for integrati

Adapting Foundation Vision-Language Models to Medical Diagnosis via Query-Driven Expert Bridging

arXiv:2505.21698v3 Announce Type: replace Abstract: Vision-language foundation models achieve promising performance in natural image classification, yet their direct application to medical imaging is

Golden Layers and Where to Find Them: Improved Knowledge Editing for Large Language Models Via Layer Gradient Analysis

arXiv:2602.20207v3 Announce Type: replace-cross Abstract: Knowledge editing in Large Language Models (LLMs) aims to update the model's prediction for a specific query to a desired target while preserv

Latent Video Prediction Learns Better World Models

arXiv:2605.15618v1 Announce Type: cross Abstract: Self-supervised video models are increasingly framed as world models, yet their evaluation remains largely confined to a single top-1 accuracy score o

researcharxiv-cs-ai

VideoGameBench: Can Vision-Language Models complete popular video games?

arXiv:2505.18134v3 Announce Type: replace Abstract: Vision-language models (VLMs) have achieved strong results on coding and math benchmarks that are challenging for humans, yet their ability to perfo

Latest open artifacts (#21): Open model bonanza! Gemma 4, DeepSeek V4, Kimi K2.6, MiMo 2.5, GLM-5.1 & others. On CAISI's V4 assessment.

model-releasesinterconnects

This article covers recent releases of open-source AI models including Gemma 4, DeepSeek V4, Kimi K2.6, MiMo 2.5, and GLM-5.1, along with discussion of CAISI's V4 model assessment framework. The piece

16 May 2026

Mini-JEPA Foundation Model Fleet Enables Agentic Hydrologic Intelligence

arXiv:2605.14120v1 Announce Type: cross Abstract: Geospatial foundation models compress multispectral observations into dense embeddings increasingly used in natural-language environmental reasoning s

Agents

Model-Adaptive Tool Necessity Reveals the Knowing-Doing Gap in LLM Tool Use

arXiv:2605.14038v1 Announce Type: new Abstract: Large language models (LLMs) increasingly act as autonomous agents that must decide when to answer directly vs. when to invoke external tools. Prior wor

agentsarxiv-cs-ai

NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces

arXiv:2605.14698v1 Announce Type: cross Abstract: Foundation models (FMs) promise to extract unified representations that generalize across downstream tasks. They have emerged across fields, including

OPT-Engine: Benchmarking the Limits of LLMs in Optimization Modeling via Complexity Scaling

arXiv:2601.19924v2 Announce Type: replace-cross Abstract: We investigate the capabilities and scalability of Large Language Models (LLMs) in optimization modeling, a domain requiring structured reason

Small Language Models (SLMs) Can Still Pack a Punch: A survey (updated 2026)

arXiv:2501.05465v2 Announce Type: replace Abstract: As foundation AI models continue to increase in size, an important question arises - is massive scale the only path forward? This survey of about 16

Unsteady Metrics and Benchmarking Cultures of AI Model Builders

arXiv:2605.14164v1 Announce Type: new Abstract: The primary way to establish and compare competencies in foundation and generative AI models has shifted from peer-reviewed literature to press releases

Another banger of a model, free for Hermes agent users via Nous Portal!

model-releasesnous-research--x

Nous Research announced the release of a new model available for free to Hermes agent users through the Nous Portal. The post suggests this is a significant model release from Nous Research, their org

CoT-Guard: Small Models for Strong Monitoring

arXiv:2605.12746v1 Announce Type: cross Abstract: Monitoring the chain-of-thought (CoT) of reasoning models is a promising approach for detecting covert misbehavior (i.e., hidden objectives) in code g

D-VLA: A High-Concurrency Distributed Asynchronous Reinforcement Learning Framework for Vision-Language-Action Models

arXiv:2605.13276v1 Announce Type: new Abstract: The rapid evolution of Embodied AI has enabled Vision-Language-Action (VLA) models to excel in multimodal perception and task execution. However, applyi

Embodied Multi-Agent Coordination by Aligning World Models Through Dialogue

arXiv:2605.12920v1 Announce Type: cross Abstract: Effective collaboration between embodied agents requires more than acting in a shared environment; it demands communication grounded in each agent's e

Local Ai

PROMETHEUS: Automating Deep Causal Research Integrating Text, Data and Models

arXiv:2605.12835v1 Announce Type: new Abstract: Large language models can extract local causal claims from text, but those claims become more useful when organized as persistent, navigable world model

local-aiarxiv-cs-ai

Query-Conditioned Test-Time Self-Training for Large Language Models

arXiv:2605.13369v1 Announce Type: cross Abstract: Large language models (LLMs) are typically deployed with fixed parameters, and their performance is often improved by allocating more computation at i

Safe Bayesian Optimization for Uncertain Correlations Matrices in Linear Models of Co-Regionalization

arXiv:2605.13302v1 Announce Type: new Abstract: This paper extends safety guarantees for multi-task Bayesian optimization with uncertain correlation matrices from intrinsic co-reginalization models to

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs

arXiv:2510.18245v3 Announce Type: replace-cross Abstract: Scaling the number of parameters and the size of training data has proven to be an effective strategy for improving large language model (LLM)

Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?

arXiv:2605.12684v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are now routinely deployed for visual understanding, generation, and curation. A substantial fraction of thes

Applications

Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner

arXiv:2510.03206v2 Announce Type: replace-cross Abstract: Diffusion language models, especially masked discrete diffusion models, have achieved great success recently. While there are some theoretical

applicationsarxiv-cs-cl

13 May 2026

Safety

Enabling clinical use of foundation models for computational pathology

arXiv:2602.22347v2 Announce Type: replace Abstract: Foundation models for computational pathology are expected to facilitate the development of high-performing, generalisable deep learning systems. Ho

safetyarxiv-cs-cv

13 May 2026

More Edits, More Stable: Understanding the Lifelong Normalization in Sequential Model Editing

arXiv:2605.11836v1 Announce Type: cross Abstract: Lifelong Model Editing aims to continuously update evolving facts in Large Language Models while preserving unrelated knowledge and general capabiliti

13 May 2026

Can We Go Beyond Visual Features? Neural Tissue Relation Modeling for Relational Graph Analysis in Non-Melanoma Skin Histology

arXiv:2512.06949v3 Announce Type: replace Abstract: Histopathology image segmentation is essential for delineating tissue structures in skin cancer diagnostics, but modeling spatial context and inter-

ColorConceptBench: A Benchmark for Probabilistic Color-Concept Understanding in Text-to-Image Models

arXiv:2601.16836v3 Announce Type: replace-cross Abstract: Text-to-image (T2I) models have advanced considerably in generating high-quality images from textual descriptions. However, their ability to a

Decomposing and Steering Functional Metacognition in Large Language Models

arXiv:2605.08942v1 Announce Type: new Abstract: Large language models (LLMs) increasingly exhibit behaviors suggesting awareness of their evaluation context, often adapting their reasoning strategies

DeformMaster: An Interactive Physics-Neural World Model for Deformable Objects from Videos

arXiv:2605.09586v1 Announce Type: new Abstract: World models for deformable objects should recover not only geometry and appearance, but also underlying physical dynamics, interaction grounding, and m

Diffusion Models are Evolutionary Algorithms

arXiv:2410.02543v3 Announce Type: replace-cross Abstract: In a convergence of machine learning and biology, we reveal that diffusion models are evolutionary algorithms. By considering evolution as a d

jNO: A JAX Library for Neural Operator and Foundation Model Training

arXiv:2605.10159v1 Announce Type: new Abstract: jNO (jax Neural Operators) is a JAX-native library for neural operators and foundation models with unified support for both data-driven and physics-info

Large Language Models as Students Who Think Aloud: Overly Coherent, Verbose, and Confident

arXiv:2602.01015v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly embedded in AI-based tutoring systems. Can they faithfully model novice reasoning and metacognitive ju

PARD-2: Target-Aligned Parallel Draft Model for Dual-Mode Speculative Decoding

arXiv:2605.08632v1 Announce Type: cross Abstract: Speculative decoding accelerates Large Language Models (LLMs) inference by using a lightweight draft model to propose candidate tokens that are verifi

researcharxiv-cs-ai

Reinforcement Learning Measurement Model

arXiv:2605.09305v1 Announce Type: cross Abstract: Interactive assessments generate sequential process data that are not well handled by conventional item response models. Existing MDP-based measuremen

Selective Deficits in LLM Mental Self-Modeling in a Behavior-Based Test of Theory of Mind

arXiv:2603.26089v2 Announce Type: replace-cross Abstract: The ability to represent oneself and others as agents with knowledge, intentions, and belief states that guide their behavior - Theory of Mind

Sparse Layers are Critical to Scaling Looped Language Models

arXiv:2605.09165v1 Announce Type: cross Abstract: Looped language models repeat a set of transformer layers through depth, reducing memory costs and providing natural early-exit points at loop boundar

researcharxiv-cs-cl

Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data

arXiv:2605.10129v1 Announce Type: new Abstract: Large language models (LLMs) rely on web-scale corpora for pre-training. The noise inherent in these datasets tends to obscure meaningful patterns and u