Search: “models”

Olmo Hybrid: From Theory to Practice and Back

model-releasesarxiv-cs-cl

arXiv:2604.03444v3 Announce Type: replace-cross Abstract: Recent work has demonstrated the potential of non-transformer language models, especially linear recurrent neural networks (RNNs) and hybrid m

OXtal: An All-Atom Diffusion Model for Organic Crystal Structure Prediction

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DGX agent

arXiv:2512.06987v2 Announce Type: replace Abstract: Accurately predicting experimentally realizable 3D molecular crystal structures from their 2D chemical graphs is a long-standing open challenge in c

model-releasesarxiv-cs-lg

20 Apr 2026

Agents

{pi}_{0.7}: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities

arXiv:2604.15483v1 Announce Type: new Abstract: We present a new robotic foundation model, called {pi}_{0.7}, that can enable strong out-of-the-box performance in a wide range of scenarios. {pi}_{0.7}

agentsarxiv-cs-lg

PixDLM: A Dual-Path Multimodal Language Model for UAV Reasoning Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.15670v1 Announce Type: new Abstract: Reasoning segmentation has recently expanded from ground-level scenes to remote-sensing imagery, yet UAV data poses distinct challenges, including obliq

Pruning Unsafe Tickets: A Resource-Efficient Framework for Safer and More Robust LLMs

model-releasesarxiv-cs-cl

arXiv:2604.15780v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in real-world applications, but even aligned models such as Mistral and LLaVA still exhibit unsafe b

SurgMotion: A Video-Native Foundation Model for Universal Understanding of Surgical Videos

arXiv:2602.05638v3 Announce Type: replace Abstract: While foundation models have advanced surgical video analysis, current approaches rely predominantly on pixel-level reconstruction objectives that w

researcharxiv-cs-cv

AlphaCNOT: Learning CNOT Minimization with Model-Based Planning

arXiv:2604.13812v1 Announce Type: new Abstract: Quantum circuit optimization is a central task in Quantum Computing, as current Noisy Intermediate Scale Quantum devices suffer from error propagation t

Dark & Stormy: Modeling Humor in Sentences from the Bulwer-Lytton Fiction Contest

arXiv:2510.24538v2 Announce Type: replace Abstract: Textual humor is enormously diverse and computational studies need to account for this range, including intentionally bad humor. In this paper, we c

Exploration and Exploitation Errors Are Measurable for Language Model Agents

arXiv:2604.13151v1 Announce Type: new Abstract: Language Model (LM) agents are increasingly used in complex open-ended decision-making tasks, from AI coding to physical AI. A core requirement in these

IUQ: Interrogative Uncertainty Quantification for Long-Form Large Language Model Generation

arXiv:2604.15109v1 Announce Type: new Abstract: Despite the rapid advancement of Large Language Models (LLMs), uncertainty quantification in LLM generation is a persistent challenge. Although recent a

applicationsarxiv-cs-cl

Model-Free Assessment of Simulator Fidelity via Quantile Curves

arXiv:2512.05024v3 Announce Type: replace-cross Abstract: As generative AI models are increasingly used to simulate real-world systems, quantifying the ``sim-to-real'' gap is critical. For each input

safetyarxiv-cs-lg

Modeling LLM Unlearning as an Asymmetric Two-Task Learning Problem

arXiv:2604.14808v1 Announce Type: new Abstract: Machine unlearning for large language models (LLMs) aims to remove targeted knowledge while preserving general capability. In this paper, we recast LLM

safetyarxiv-cs-cl

The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure

arXiv:2604.14197v1 Announce Type: new Abstract: Large language model (LLM) performance depends heavily on prompt design, yet prompt construction is often described and applied inconsistently. Our purp

safetyarxiv-cs-cl

GeoBridge: A Semantic-Anchored Multi-View Foundation Model Bridging Images and Text for Geo-Localization

model-releasesarxiv-cs-cv

arXiv:2512.02697v3 Announce Type: replace Abstract: Cross-view geo-localization infers a location by retrieving geo-tagged reference images that visually correspond to a query image. However, the trad

How Can We Synthesize High-Quality Pretraining Data? A Systematic Study of Prompt Design, Generator Model, and Source Data

arXiv:2604.13977v1 Announce Type: new Abstract: Synthetic data is a standard component in training large language models, yet systematic comparisons across design dimensions, including rephrasing stra

Linear Probe Accuracy Scales with Model Size and Benefits from Multi-Layer Ensembling

arXiv:2604.13386v1 Announce Type: new Abstract: Linear probes can detect when language models produce outputs they 'know' are wrong, a capability relevant to both deception and reward hacking. However

researcharxiv-cs-lg

Tutorials

Modeling Student Learning with 3.8 Million Program Traces

arXiv:2510.05056v2 Announce Type: replace Abstract: As programmers write code, they often edit and retry multiple times, creating rich 'interaction traces' that reveal how they approach coding tasks a

tutorialsarxiv-cs-lg

Native Hybrid Attention for Efficient Sequence Modeling

arXiv:2510.07019v3 Announce Type: replace Abstract: Transformers excel at sequence modeling but face quadratic complexity, while linear attention offers improved efficiency but often compromises recal

Cognition-Inspired Dual-Stream Semantic Enhancement for Vision-Based Dynamic Emotion Modeling

arXiv:2604.12777v1 Announce Type: cross Abstract: The human brain constructs emotional percepts not by processing facial expressions in isolation, but through a dynamic, hierarchical integration of se

CycloneMAE: A Scalable Multi-Task Learning Model for Global Tropical Cyclone Probabilistic Forecasting

arXiv:2604.12180v1 Announce Type: cross Abstract: Tropical cyclones (TCs) rank among the most destructive natural hazards, yet their forecasting faces fundamental trade-offs: numerical weather predict

How memory can affect collective and cooperative behaviors in an LLM-Based Social Particle Swarm

arXiv:2604.12250v1 Announce Type: new Abstract: This study examines how model-specific characteristics of Large Language Model (LLM) agents, including internal alignment, shape the effect of memory on

Mantis: A Foundation Model for Mechanistic Disease Forecasting

arXiv:2508.12260v5 Announce Type: replace Abstract: Infectious disease forecasting in novel outbreaks or low-resource settings is hampered by the need for large disease and covariate data sets, bespok

applicationsarxiv-cs-ai

ParetoBandit: Budget-Paced Adaptive Routing for Non-Stationary LLM Serving

model-releasesarxiv-cs-cl

arXiv:2604.00136v2 Announce Type: replace-cross Abstract: Multi-model LLM serving operates in a non-stationary, noisy environment: providers revise pricing, model quality can shift or regress without

Speaker effects in language comprehension: An integrative model of language and speaker processing

arXiv:2412.07238v3 Announce Type: replace Abstract: The identity of a speaker influences language comprehension through modulating perception and expectation. This review explores speaker effects and

AdaQE-CG: Adaptive Query Expansion for Web-Scale Generative AI Model and Data Card Generation

arXiv:2604.09617v1 Announce Type: new Abstract: Transparent and standardized documentation is essential for building trustworthy generative AI (GAI) systems. However, existing automated methods for ge

Bootstrapping Video Semantic Segmentation Model via Distillation-assisted Test-Time Adaptation

arXiv:2604.10950v1 Announce Type: new Abstract: Fully supervised Video Semantic Segmentation (VSS) relies heavily on densely annotated video data, limiting practical applicability. Alternatively, appl

applicationsarxiv-cs-cv

Breaking the KV Cache Bottleneck: Fan Duality Model Achieves O(1) Decode Memory with Superior Associative Recall

arXiv:2604.07716v2 Announce Type: replace Abstract: We present FDM (Fan Duality Model), a linear sequence architecture that resolves the fundamental tension between memory efficiency and associative r

researcharxiv-cs-lg

Computational Implementation of a Model of Category-Theoretic Metaphor Comprehension

arXiv:2604.10035v1 Announce Type: cross Abstract: In this study, we developed a computational implementation for a model of metaphor comprehension based on the theory of indeterminate natural transfor

CROP: Conservative Reward for Model-based Offline Policy Optimization

arXiv:2310.17245v2 Announce Type: replace-cross Abstract: Offline reinforcement learning (RL) aims to optimize a policy using collected data without online interactions. Model-based approaches are par

Efficient Process Reward Modeling via Contrastive Mutual Information

arXiv:2604.10660v1 Announce Type: cross Abstract: Recent research has devoted considerable effort to verifying the intermediate reasoning steps of chain-of-thought (CoT) trajectories using process rew

Tutorials

EviCare: Enhancing Diagnosis Prediction with Deep Model-Guided Evidence for In-Context Reasoning

arXiv:2604.10455v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled promising progress in diagnosis prediction from electronic health records (EHRs). However,

tutorialsarxiv-cs-cl

Fake-HR1: Rethinking Reasoning of Vision Language Model for Synthetic Image Detection

arXiv:2602.10042v3 Announce Type: replace-cross Abstract: Recent studies have demonstrated that incorporating Chain-of-Thought (CoT) reasoning into the detection process can enhance a model's ability

HFI: A unified framework for training-free detection and implicit watermarking of latent diffusion model generated images

arXiv:2412.20704v2 Announce Type: replace Abstract: Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-genera

researcharxiv-cs-cv

Agents

Human Centered Non Intrusive Driver State Modeling Using Personalized Physiological Signals in Real World Automated Driving

arXiv:2604.11549v1 Announce Type: cross Abstract: In vehicles with partial or conditional driving automation (SAE Levels 2-3), the driver remains responsible for supervising the system and responding

agentsarxiv-cs-lg

Local Ai

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

arXiv:2604.11513v1 Announce Type: cross Abstract: We review recent advances in machine-learning (ML) force-field methods for large-scale Landau-Lifshitz-Gilbert (LLG) simulations of metallic spin syst

local-aiarxiv-cs-lg

NeuroFlow: Toward Unified Visual Encoding and Decoding from Neural Activity

arXiv:2604.09817v1 Announce Type: new Abstract: Visual encoding and decoding models act as gateways to understanding the neural mechanisms underlying human visual perception. Typically, visual encodin

researcharxiv-cs-lg

Tutorials

Quantum-Gated Task-interaction Knowledge Distillation for Pre-trained Model-based Class-Incremental Learning

arXiv:2604.11112v1 Announce Type: cross Abstract: Class-incremental learning (CIL) aims to continuously accumulate knowledge from a stream of tasks and construct a unified classifier over all seen cla

tutorialsarxiv-cs-cv

Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling

arXiv:2512.12675v2 Announce Type: replace-cross Abstract: Subject-driven image generation has advanced from single- to multi-subject composition, while neglecting distinction, the ability to distingui

STU-PID: Steering Token Usage via PID Controller for Efficient Large Language Model Reasoning

arXiv:2506.18831v2 Announce Type: replace Abstract: Large Language Models employing extended chain-of-thought (CoT) reasoning often suffer from the overthinking phenomenon, generating excessive and re

TempusBench: An Evaluation Framework for Time-Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2604.11529v1 Announce Type: new Abstract: Foundation models have transformed natural language processing and computer vision, and a rapidly growing literature on time-series foundation models (T

Valence-Arousal Subspace in LLMs: Circular Emotion Geometry and Multi-Behavioral Control

arXiv:2604.03147v2 Announce Type: replace-cross Abstract: We present a method to identify a valence-arousal (VA) subspace within large language model representations. From 211k emotion-labeled texts,

A Mathematical Framework for Temporal Modeling and Counterfactual Policy Simulation of Student Dropout

arXiv:2604.08874v1 Announce Type: cross Abstract: This study proposes a temporal modeling framework with a counterfactual policy-simulation layer for student dropout in higher education, using LMS eng

AMO-ENE: Attention-based Multi-Omics Fusion Model for Outcome Prediction in Extra Nodal Extension and HPV-associated Oropharyngeal Cancer

arXiv:2604.09280v1 Announce Type: cross Abstract: Extranodal extension (ENE) is an emerging prognostic factor in human papillomavirus (HPV)-associated oropharyngeal cancer (OPC), although it is curren

researcharxiv-cs-cv

An Adaptive Model Selection Framework for Demand Forecasting under Horizon-Induced Degradation to Support Business Strategy and Operations

arXiv:2602.13939v3 Announce Type: replace-cross Abstract: Business environments characterized by intermittent demand, high variability, and multi-step planning horizons require forecasting policies th

Demystifying Mergeability: Interpretable Properties to Predict Model Merging Success

arXiv:2601.22285v4 Announce Type: replace Abstract: Model merging combines knowledge from separately fine-tuned models, yet success factors remain poorly understood. While recent work treats mergeabil

safetyarxiv-cs-lg

Graph Defense Diffusion Model

arXiv:2501.11568v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) are highly vulnerable to adversarial attacks, which can greatly degrade their performance. Existing graph purification

applicationsarxiv-cs-lg

Listener-Rewarded Thinking in VLMs for Image Preferences

arXiv:2506.22832v3 Announce Type: replace-cross Abstract: Training robust and generalizable reward models for human visual preferences is essential for aligning text-to-image and text-to-video generat

LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving

arXiv:2604.08719v1 Announce Type: cross Abstract: Recent years have seen remarkable progress in autonomous driving, yet generalization to long-tail and open-world scenarios remains a major bottleneck