Search: “models”

Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry

arXiv:2512.11855v2 Announce Type: replace-cross Abstract: Enforcing exact symmetry in machine learning models often yields significant gains in scientific applications, serving as a powerful inductive

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AIS: Adaptive Importance Sampling for Quantized RL

DGX agent

arXiv:2605.13907v1 Announce Type: cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is dominated by the cost of rollout generation, which has motivated the use of low-precis

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15 May 2026

AMiD: Knowledge Distillation for LLMs with alpha-mixture Assistant Distribution

arXiv:2510.15982v3 Announce Type: replace-cross Abstract: Autoregressive large language models (LLMs) have achieved remarkable improvement across many tasks but incur high computational and memory cos

APWA: A Distributed Architecture for Parallelizable Agentic Workflows

arXiv:2605.15132v1 Announce Type: new Abstract: Autonomous multi-agent systems based on large language models (LLMs) have demonstrated remarkable abilities in independently solving complex tasks in a

AVEX: What Matters for Animal Vocalization Encoding

arXiv:2508.11845v3 Announce Type: replace-cross Abstract: Bioacoustics, the study of sounds produced by living organisms, plays a vital role in conservation, biodiversity monitoring, and behavioral st

Bad Seeing or Bad Thinking? Rewarding Perception for Vision-Language Reasoning

arXiv:2605.14054v1 Announce Type: new Abstract: Achieving robust perception-reasoning synergy is a central goal for advanced Vision-Language Models (VLMs). Recent advancements have pursued this goal v

Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance

arXiv:2605.15012v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has achieved great success in developing Large Language Models (LLMs) with chain-of-thought roll

Bridging the Rural Healthcare Gap: A Cascaded Edge-Cloud Architecture for Automated Retinal Screening

arXiv:2605.14108v1 Announce Type: cross Abstract: Diabetic Retinopathy (DR) is one of the leading causes of preventable blindness, yet rural regions often lack the specialists and infrastructure neede

local-aiarxiv-cs-ai

Tutorials

Characterizing the visual representation of objects from the child's view

arXiv:2605.14990v1 Announce Type: new Abstract: Children acquire object category representations from their everyday experiences in the first few years of life. What do the inputs to this learning pro

tutorialsarxiv-cs-cv

CHASM: Cross-frequency Harmonized Axis-Separable Mixing for Spectral Token Operators

arXiv:2605.14727v1 Announce Type: new Abstract: Spectral token mixers based on Fourier transforms provide an efficient way to model global interactions in visual feature maps. Existing designs often e

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ChromaFlow: A Negative Ablation Study of Orchestration Overhead in Tool-Augmented Agent Evaluation

arXiv:2605.14102v1 Announce Type: new Abstract: Autonomous language-model agents increasingly combine planning, tool use, document processing, browsing, code execution, and verification loops. These c

CoRDS: Coreset-based Representative and Diverse Selection for Streaming Video Understanding

arXiv:2605.14310v1 Announce Type: new Abstract: Streaming video understanding with large vision-language models (VLMs) requires a compact memory that can support future reasoning over an ever-growing

researcharxiv-cs-cv

CSI-JEPA: Towards Foundation Representations for Ubiquitous Sensing with Minimal Supervision

arXiv:2605.14171v1 Announce Type: new Abstract: Channel state information (CSI) provides a widely available sensing modality for human and environment perception, but existing CSI sensing models usual

applicationsarxiv-cs-lg

Deepchecks: Evaluating Retrieval-Augmented Generation (RAG)

arXiv:2605.14488v1 Announce Type: new Abstract: Large Language Models (LLMs) augmented with Retrieval-Augmented Generation (RAG) techniques are revolutionizing applications across multiple domains, su

DermAgent: A Self-Reflective Agentic System for Dermatological Image Analysis with Multi-Tool Reasoning and Traceable Decision-Making

arXiv:2605.14403v1 Announce Type: new Abstract: Dermatological diagnosis requires integrating fine-grained visual perception with expert clinical knowledge. Although Multimodal Large Language Models (

agentsarxiv-cs-cv

Do We Really Need External Tools to Mitigate Hallucinations? SIRA: Shared-Prefix Internal Reconstruction of Attribution

arXiv:2605.14621v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate when language priors dominate weak or ambiguous visual evidence. Existing contrastive decoding

DSSP: Diffusion State Space Policy with Full-History Encoding

arXiv:2605.14598v1 Announce Type: new Abstract: Diffusion-based imitation learning has shown strong promise for robot manipulation. However, most existing policies condition only on the current observ

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Dual-Dimensional Consistency: Balancing Budget and Quality in Adaptive Inference-Time Scaling

arXiv:2605.15100v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable abilities in reasoning. However, maximizing their potential through inference-time scaling fac

Dynamic Latent Routing

arXiv:2605.14323v1 Announce Type: cross Abstract: We investigate the temporal concatenation of sub-policies in Markov Decision Processes (MDP) with time-varying reward functions. We introduce General

Dynamics of the Transformer Residual Stream: Coupling Spectral Geometry to Network Topology

arXiv:2605.14258v1 Announce Type: cross Abstract: Large language models are remarkably capable, yet how computation propagates through their layers remains poorly understood. A growing line of work tr

applicationsarxiv-cs-ai

Efficient Generative Retrieval for E-commerce Search with Semantic Cluster IDs and Expert-Guided RL

arXiv:2605.14434v1 Announce Type: cross Abstract: Generative retrieval offers a promising alternative by unifying the fragmented multi-stage retrieval process into a single end-to-end model. However,

Efficient Multi-objective Prompt Optimization via Pure-exploration Bandits

arXiv:2605.14553v1 Announce Type: cross Abstract: Prompt engineering has become central to eliciting the capabilities of large language models (LLMs). At its core lies prompt selection -- efficiently

Evidential Reasoning Advances Interpretable Real-World Disease Screening

arXiv:2605.15171v1 Announce Type: cross Abstract: Disease screening is critical for early detection and timely intervention in clinical practice. However, most current screening models for medical ima

applicationsarxiv-cs-ai

Explainable Detection of Depression Status Shifts from User Digital Traces

arXiv:2605.14995v1 Announce Type: new Abstract: Every day, users generate digital traces (e.g., social media posts, chats, and online interactions) that are inherently timestamped and may reflect aspe

FactNet: A Billion-Scale Knowledge Graph for Multilingual Factual Grounding

arXiv:2602.03417v2 Announce Type: replace Abstract: Large language models hallucinate factual claims and struggle to ground their outputs in retrievable evidence, particularly in non-English languages

researcharxiv-cs-cl

Feature Visualization Recovers Known Cortical Selectivity from TRIBE v2

arXiv:2605.13904v1 Announce Type: cross Abstract: Brain encoder models predict cortical fMRI responses from the internal activations of pretrained vision and language networks, and are typically evalu

From Plans to Pixels: Learning to Plan and Orchestrate for Open-Ended Image Editing

arXiv:2605.15181v1 Announce Type: new Abstract: Modern image editing models produce realistic results but struggle with abstract, multi step instructions (e.g., ``make this advertisement more vegetari

agentsarxiv-cs-cv

Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs

arXiv:2410.06431v5 Announce Type: replace Abstract: Accurate uncertainty quantification in large language models (LLMs) is essential for reliable confidence estimation, yet fine-tuned LLMs often becom

Generative Floor Plan Design with LLMs via Reinforcement Learning with Verifiable Rewards

arXiv:2605.14117v1 Announce Type: cross Abstract: An AI system for professional floor plan design must precisely control room dimensions and areas while respecting the desired connectivity between roo

GeoViSTA: Geospatial Vision-Tabular Transformer for Multimodal Environment Representation

arXiv:2605.14406v1 Announce Type: cross Abstract: Large-scale pretraining on Earth observation imagery has yielded powerful representations of the natural and built environment. However, most existing

local-aiarxiv-cs-cv

Graphs of Research: Citation Evolution Graphs as Supervision for Research Idea Generation

arXiv:2605.14790v1 Announce Type: cross Abstract: Research idea generation is the innovation-driving step of automated scientific research. Recently, large language models (LLMs) have shown potential

Hand-in-the-Loop: Improving Dexterous VLA via Seamless Interventional Correction

arXiv:2605.15157v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are prone to compounding errors in dexterous manipulation, where high-dimensional action spaces and contact-rich d

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Head Forcing: Long Autoregressive Video Generation via Head Heterogeneity

arXiv:2605.14487v1 Announce Type: cross Abstract: Autoregressive video diffusion models support real-time synthesis but suffer from error accumulation and context loss over long horizons. We discover

Tutorials

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization

arXiv:2605.14200v1 Announce Type: new Abstract: Recent frontier large language models predominantly rely on Mixture-of-Experts (MoE) architectures. Despite empirical progress, there is still no princi

tutorialsarxiv-cs-lg

IsoNet: Spatially-aware audio-visual target speech extraction in complex acoustic environments

arXiv:2605.14736v1 Announce Type: cross Abstract: Target speech extraction remains difficult for compact devices because monaural neural models lack spatial evidence and classical beamformers lose res

Lang2MLIP: End-to-End Language-to-Machine Learning Interatomic Potential Development with Autonomous Agentic Workflows

arXiv:2605.14527v1 Announce Type: new Abstract: Developing machine learning interatomic potentials (MLIPs) for complex materials systems remains challenging because it requires expertise in atomistic

agentsarxiv-cs-lg

Language Generation as Optimal Control: Closed-Loop Diffusion in Latent Control Space

arXiv:2605.14531v1 Announce Type: new Abstract: This work reformulates language generation as a stochastic optimal control problem, providing a unified theoretical perspective to analyze autoregressiv

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Tutorials

Language-Induced Priors for Domain Adaptation

arXiv:2605.14301v1 Announce Type: new Abstract: Domain adaptation faces a fundamental paradox in the cold-start regime. When target data is scarce, statistical methods fail to distinguish relevant sou

tutorialsarxiv-cs-lg

LATERN: Test-Time Context-Aware Explainable Video Anomaly Detection

arXiv:2605.15054v1 Announce Type: new Abstract: Vision-language models (VLMs) have recently emerged as a promising paradigm for video anomaly detection (VAD) due to their strong visual reasoning abili

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LEMON: Learning Executable Multi-Agent Orchestration via Counterfactual Reinforcement Learning

arXiv:2605.14483v1 Announce Type: new Abstract: Large language models (LLMs) have become a strong foundation for multi-agent systems, but their effectiveness depends heavily on orchestration design. A

local-aiarxiv-cs-ai

MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis

arXiv:2601.20173v2 Announce Type: replace Abstract: We present a new nonlinear dimensionality reduction method, MAPLE, that enhances UMAP by improving manifold modeling. MAPLE employs a self-supervise

Masked Autoencoders with Limited Data: Does It Work? A Fine-Grained Bioacoustics Case Study

arXiv:2605.14031v1 Announce Type: cross Abstract: Bioacoustic recognition requires fine-grained acoustic understanding to distinguish similar-sounding species. However, many large-scale data repositor

applicationsarxiv-cs-cv

Matrix-Space Reinforcement Learning for Reusing Local Transition Geometry

arXiv:2605.14304v1 Announce Type: cross Abstract: Compositional generalization in sequential decision-making requires identifying which parts of prior rollouts remain useful for new tasks. Existing me

local-aiarxiv-cs-ai

Medical Report Generation: A Hierarchical Task Structure-Based Cross-Modal Causal Intervention Framework

arXiv:2511.02271v2 Announce Type: replace Abstract: Medical Report Generation (MRG) is a key part of modern medical diagnostics, as it automatically generates reports from radiological images to reduc

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MemLineage: Lineage-Guided Enforcement for LLM Agent Memory

arXiv:2605.14421v1 Announce Type: cross Abstract: We introduce MemLineage, a defense for LLM agent memory that attaches both cryptographic provenance and LLM-mediated derivation lineage to every entry

MetaMoE: Diversity-Aware Proxy Selection for Privacy-Preserving Mixture-of-Experts Unification

arXiv:2605.14289v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models scale capacity by combining specialized experts, but most existing approaches assume centralized access to training da

MHSA: A Lightweight Framework for Mitigating Hallucinations via Steered Attention in LVLMs

arXiv:2605.14966v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have achieved remarkable performance across diverse multimodal tasks, yet they continue to suffer from hallucinat

MiVE: Multiscale Vision-language features for reference-guided video Editing

arXiv:2605.14664v1 Announce Type: new Abstract: Reference-guided video editing takes a source video, a text instruction, and a reference image as inputs, requiring the model to faithfully apply the in

researcharxiv-cs-cv