Search: “models”

I have to eat crow on this, in light of further information. whatever OpenAI spent on Erdos using a new model, apparently you can get GPT 5.…

model-releasesgary-marcus--x

I have to eat crow on this, in light of further information. whatever OpenAI spent on Erdos using a new model, apparently you can get GPT 5.5 to do something similar; @emollick’s presumably estimates

Model Releases

Linear Dynamics in the RLVR Training of Large Language Models

DGX agent

arXiv:2601.04537v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has driven significant performance gains in reasoning-oriented large language models (LL

model-releasesarxiv-cs-cl

22 May 2026

One prompt is not enough: Instruction Sensitivity Undermines Embedding Model Evaluation

arXiv:2605.22544v1 Announce Type: new Abstract: Instruction embedding models have become common among state-of-the-art models, however are evaluated using a single prompt per task. The single-point ev

researcharxiv-cs-cl

Probabilistic Attribution For Large Language Models

arXiv:2605.21726v1 Announce Type: new Abstract: The generative nature of Large Language Models (LLMs) is reflected in the conditional probabilities they compute to sample each response token given the

researcharxiv-cs-cl

Reflective Prompt Tuning through Language Model Function-Calling

arXiv:2605.21781v1 Announce Type: new Abstract: Large language models (LLMs) have become increasingly capable of following instructions and complex reasoning, making prompting a flexible interface for

stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation

arXiv:2605.21800v1 Announce Type: cross Abstract: World models are central to building agents that can reason, plan, and generalize beyond their training data. However, research on world models is cur

researcharxiv-cs-ro

Thermo-VL: Extending Vision-Language Models to Thermal Infrared Perception

arXiv:2605.21882v1 Announce Type: new Abstract: Vision-language models (VLMs) often fail under low illumination because their visual grounding is learned predominantly from RGB imagery, whereas therma

Do LLMs Know What Luxembourgish Borrows? Probing Lexical Neology in Low-Resource Multilingual Models

arXiv:2605.21227v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for writing assistance in small contact languages, yet it is unclear whether they respect community n

Do Vision--Language Models Understand 3D Scenes or Just Catalogue Objects?

arXiv:2605.20448v1 Announce Type: new Abstract: Vision--language models reliably name objects in a scene, but do they represent the 3D layout those objects inhabit? We introduce a 3,034-sample human-c

Post-Hoc Understanding of Metaphor Processing in Decoder-Only Language Models via Conditional Scale Entropy

arXiv:2605.21391v1 Announce Type: new Abstract: Metaphor requires a language model to resolve a token whose contextual meaning diverges from its basic literal sense. Understanding how transformer mode

Agents

STELLAR: Scaling 3D Perception Large Models for Autonomous Driving

arXiv:2605.20390v1 Announce Type: new Abstract: Model scaling has demonstrated remarkable success through large-scale training on diverse datasets. It remains an open question whether the same paradig

agentsarxiv-cs-cv

SymbolicLight V1: Spike-Gated Dual-Path Language Modeling with High Activation Sparsity and Sub-Billion-Scale Pre-Training Evidence

arXiv:2605.21333v1 Announce Type: new Abstract: Natively trained spiking language models struggle to combine Transformer-like language quality, stable multi-domain pre-training, and high activation sp

TempGlitch: Evaluating Vision-Language Models for Temporal Glitch Detection in Gameplay Videos

arXiv:2605.21443v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly being explored for video game quality assurance, especially gameplay glitch detection. Most existing eval

The Visual Iconicity Challenge: Evaluating Vision-Language Models on Sign Language Form-Meaning Mapping

arXiv:2510.08482v3 Announce Type: replace-cross Abstract: Iconicity, the resemblance between linguistic form and meaning, is pervasive in signed languages, offering a natural testbed for visual ground

A Hybrid Modeling Framework for Crop Prediction Tasks via Dynamic Parameter Calibration and Multi-Task Learning

arXiv:2603.15411v2 Announce Type: replace Abstract: Accurate prediction of crop states (e.g., phenology stages and cold hardiness) is essential for timely farm management decisions such as irrigation,

Addressing prior dependence in hierarchical Bayesian modeling for PTA data analysis II: Noise and SGWB inference through parameter decorrelation

model-releasesarxiv-cs-lg

arXiv:2511.01959v2 Announce Type: replace-cross Abstract: Pulsar Timing Arrays (PTA) provide a powerful framework to measure low-frequency gravitational waves, but accuracy and robustness of the resul

Distributional Energy-Based Models for Uncertainty-Aware Structured LLM Reasoning

arXiv:2605.18871v1 Announce Type: cross Abstract: When Large Language Models produce structured outputs such as travel plans, code solutions, or multi-step proofs, individual reasoning steps may appea

Fine-Grained Benchmark Generation for Comprehensive Evaluation of Foundation Models

arXiv:2605.18824v1 Announce Type: cross Abstract: Evaluation of foundation models often rely on aggregate scores from benchmarks that lack comprehensive coverage and metadata for a fine-grained evalua

FineBench: Benchmarking and Enhancing Vision-Language Models for Fine-grained Human Activity Understanding

arXiv:2605.19846v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated remarkable capabilities in general video understanding, yet they often struggle with the fine-grained

HELLoRA: Hot Experts Layer-Level Low-Rank Adaptation for Mixture-of-Experts Models

arXiv:2605.18795v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) dominates parameter-efficient fine-tuning of large language models, yet most variants target dense architectures. Mixture-o

LIFT and PLACE: A Simple, Stable, and Effective Knowledge Distillation Framework for Lightweight Diffusion Models

arXiv:2605.19729v1 Announce Type: cross Abstract: We demonstrate that in knowledge distillation for diffusion models, the teacher network's highly complex denoising process - stemming from its substan

MixRea: Benchmarking Explicit-Implicit Reasoning in Large Language Models

arXiv:2605.20128v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into high-stakes decision-making. Inspired by the theory of inattentional blindness in human co

OpenCompass: A Universal Evaluation Platform for Large Language Models

arXiv:2605.19276v1 Announce Type: new Abstract: In recent years, the field of artificial intelligence has undergone a paradigm shift from task-specific small-scale models to general-purpose large lang

Prompting language influences diagnostic reasoning and accuracy of large language models

arXiv:2605.19173v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly explored for clinical decision support, yet most evaluations are conducted in English, leaving their relia

RE-VLM: Event-Augmented Vision-Language Model for Scene Understanding

arXiv:2605.19329v1 Announce Type: cross Abstract: Conventional vision-language models (VLMs) struggle to interpret scenes captured under adverse conditions (e.g., low light, high dynamic range, or fas

Safety

Stitched Value Model for Diffusion Alignment

arXiv:2605.19804v1 Announce Type: cross Abstract: For practical use, diffusion- or flow-based generative models must be aligned with task-specific rewards, such as prompt fidelity or aesthetic prefere

safetyarxiv-cs-ai

Towards Data-Efficient Video Pre-training with Frozen Image Foundation Models

arXiv:2605.19137v1 Announce Type: new Abstract: Video foundation models achieve strong performance across many video understanding tasks, but typically require large-scale pre-training on massive vide

researcharxiv-cs-cv

Tutorials

WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling

arXiv:2602.03924v2 Announce Type: replace-cross Abstract: Deep learning has revolutionized weather forecasting, but many challenges remain, including climate modeling. Moreover, the current landscape

tutorialsarxiv-cs-ai

A-ProS: Towards Reliable Autonomous Programming Through Multi-Model Feedback

arXiv:2605.18073v1 Announce Type: cross Abstract: Large Language Models (LLMs) demonstrate strong potential for automated code generation, yet their ability to iteratively refine solutions using execu

AgroCoT: A Chain-of-Thought Benchmark for Evaluating Reasoning in Vision-Language Models for Agriculture

arXiv:2511.23253v3 Announce Type: replace Abstract: Recent advancements in Vision-Language Models (VLMs) have significantly impacted various industries. In agriculture, these multimodal capabilities h

Ancient Greek to Modern Greek Machine Translation: A Novel Benchmark and Fine-Tuning Experiments on LLMs and NMT Models

arXiv:2605.18504v1 Announce Type: new Abstract: Machine Translation (MT) for Ancient Greek (AG) to Modern Greek (MG) is a low-resource task, constrained by the lack of large-scale, high-quality parall

Beacon: Single-Turn Diagnosis and Mitigation of Latent Sycophancy in Large Language Models

arXiv:2510.16727v2 Announce Type: replace-cross Abstract: Large language models internalize a structural trade-off between truthfulness and obsequious flattery, emerging from reward optimization that

Safety

CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials

arXiv:2605.17254v1 Announce Type: new Abstract: Property prediction and inverse structural design of catalytic materials are typically modeled as two independent tasks: the former predicts target prop

safetyarxiv-cs-ai

Safety

Factored Causal Representation Learning for Robust Reward Modeling in RLHF

arXiv:2601.21350v2 Announce Type: replace Abstract: A reliable reward model is essential for aligning large language models with human preferences through reinforcement learning from human feedback. H

safetyarxiv-cs-lg

Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization

arXiv:2605.17693v1 Announce Type: cross Abstract: Structure-based drug design has been accelerated by pocket-aware 3D generative models, yet most methods primarily fit the training distribution and ma

FormuLLA: A Large Language Model Approach to Generating Novel 3D Printable Formulations

arXiv:2601.02071v3 Announce Type: replace Abstract: Pharmaceutical three-dimensional (3D) printing is an advanced fabrication technology with the potential to enable truly personalised dosage forms. R

GAMMA: Global Bit Allocation for Mixed-Precision Models under Arbitrary Budgets

arXiv:2605.18475v1 Announce Type: cross Abstract: Mixed-precision quantization improves the budget--accuracy trade-off for large language models (LLMs) by allocating more bits to sensitive modules. Ho

HEED: Density-Weighted Residual Alignment for Hybrid Vision-Language Model Distillation

arXiv:2605.17093v1 Announce Type: cross Abstract: Distilling vision-language models into faster hybrid architectures, such as 3:1 Mamba-2/attention mixes, is now standard practice for making inference

Hunt Instead of Wait: Evaluating Deep Data Research on Large Language Models

arXiv:2602.02039v2 Announce Type: replace Abstract: The agency expected of Agentic Large Language Models goes beyond answering correctly, requiring autonomy to set goals and decide what to explore. We

Identifiable Token Correspondence for World Models

arXiv:2605.16457v1 Announce Type: cross Abstract: Transformer-based world models have shown strong performance in visual reinforcement learning, but often suffer from temporal inconsistency in long-ho

KairosHope: A Next-Generation Time-Series Foundation Model for Specialized Classification via Dual-Memory Architecture

arXiv:2605.18657v1 Announce Type: cross Abstract: Time Series Foundation Models (TSFMs) have demonstrated notable success in general-purpose forecasting tasks; however, their adaptation to specialized

Local Ai

LAST-RAG: Literature-Anchored Stochastic Trajectory Retrieval-Augmented Generation for Knowledge-Conditioned Degradation Model Selection

arXiv:2605.17902v1 Announce Type: new Abstract: Stochastic-process-based degradation modeling is a core approach for estimating the distribution of remaining useful life (RUL); however, the selection

local-aiarxiv-cs-ai

Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting

arXiv:2510.10528v3 Announce Type: replace Abstract: Large reasoning models (LRMs) have demonstrated remarkable proficiency in tackling complex tasks through step-by-step thinking. However, this length

Multilingual OCR-Aware Fine-Tuning and Prompt-Guided Chain-of-Thought Reasoning for Multimodal Large Language Models

arXiv:2605.16409v1 Announce Type: cross Abstract: Optical character recognition (OCR) and multilingual text understanding remain major failure modes of multimodal large language models (MLLMs), partic

Seeing Together:Multi-Robot Cooperative Egocentric Spatial Reasoning with Multimodal Large Language Models

arXiv:2605.18431v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have made substantial progress in egocentric video understanding, but their ability to reason cooperatively fro

Statistical Hand Shape Modeling from Clinical CT Scans Using Deep Learning and Implicit Skinning

arXiv:2605.16980v1 Announce Type: new Abstract: Accurate segmentation and statistical shape modeling of hand anatomy have significant implications for medical diagnostics, ergonomics, and biomechanics

researcharxiv-cs-cv

Towards Long-Lived Robots: Continual Learning VLA Models via Reinforcement Fine-Tuning

model-releasesarxiv-cs-ro

arXiv:2602.10503v2 Announce Type: replace Abstract: Pretrained on large-scale and diverse datasets, VLA models demonstrate strong generalization and adaptability as general-purpose robotic policies. H

VideoNeuMat: Neural Material Extraction from Generative Video Models

arXiv:2602.07272v2 Announce Type: replace Abstract: Creating photorealistic materials for 3D rendering requires exceptional artistic skill. Generative models for materials could help, but are currentl

researcharxiv-cs-cv