Search: “models”

When Does LLM Self-Correction Help? A Control-Theoretic Markov Diagnostic and Verify-First Intervention

arXiv:2604.22273v1 Announce Type: new Abstract: Iterative self-correction is widely used in agentic LLM systems, but when repeated refinement helps versus hurts remains unclear. We frame self-correcti

27 Apr 2026

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Model Releases

Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation

DGX agent

arXiv:2604.22102v1 Announce Type: cross Abstract: Many robotic tasks are unforgiving; a single mistake in a dynamic throw can lead to unacceptable delays or unrecoverable failure. To mitigate this, we

model-releasesarxiv-cs-ai

27 Apr 2026

APCoTTA: Continual Test-Time Adaptation for Semantic Segmentation of Airborne LiDAR Point Clouds

arXiv:2505.09971v3 Announce Type: replace Abstract: Airborne laser scanning (ALS) point cloud semantic segmentation is a fundamental task for large-scale 3D scene understanding. Fixed models deployed

ATATA: One Algorithm to Align Them All

arXiv:2601.11194v2 Announce Type: replace Abstract: We suggest a new multi-modal algorithm for joint inference of paired structurally aligned samples with Rectified Flow models. While some existing me

safetyarxiv-cs-cv

Beyond N-gram: Data-Aware X-GRAM Extraction for Efficient Embedding Parameter Scaling

arXiv:2604.21724v1 Announce Type: new Abstract: Large token-indexed lookup tables provide a compute-decoupled scaling path, but their practical gains are often limited by poor parameter efficiency and

Calibeating Prediction-Powered Inference

arXiv:2604.21260v1 Announce Type: cross Abstract: We study semisupervised mean estimation with a small labeled sample, a large unlabeled sample, and a black-box prediction model whose output may be mi

Counterfactual Segmentation Reasoning: Diagnosing and Mitigating Pixel-Grounding Hallucination

arXiv:2506.21546v4 Announce Type: replace-cross Abstract: Segmentation Vision-Language Models (VLMs) have significantly advanced grounded visual understanding, yet they remain prone to pixel-grounding

Applications

Cross-Domain Data Selection and Augmentation for Automatic Compliance Detection

arXiv:2604.21469v1 Announce Type: new Abstract: Automating the detection of regulatory compliance remains a challenging task due to the complexity and variability of legal texts. Models trained on one

applicationsarxiv-cs-cl

Decoupled DiLoCo for Resilient Distributed Pre-training

arXiv:2604.21428v1 Announce Type: new Abstract: Modern large-scale language model pre-training relies heavily on the single program multiple data (SPMD) paradigm, which requires tight coupling across

Dr. Assistant: Enhancing Clinical Diagnostic Inquiry via Structured Diagnostic Reasoning Data and Reinforcement Learning

arXiv:2601.13690v2 Announce Type: replace Abstract: Clinical Decision Support Systems (CDSSs) provide reasoning and inquiry guidance for physicians, yet they face notable challenges, including high ma

Drug Synergy Prediction via Residual Graph Isomorphism Networks and Attention Mechanisms

arXiv:2604.21473v1 Announce Type: cross Abstract: In the treatment of complex diseases, treatment regimens using a single drug often yield limited efficacy and can lead to drug resistance. In contrast

Local Ai

DWTSumm: Discrete Wavelet Transform for Document Summarization

arXiv:2604.21070v1 Announce Type: new Abstract: Summarizing long, domain-specific documents with large language models (LLMs) remains challenging due to context limitations, information loss, and hall

local-aiarxiv-cs-cl

Efficient Logic Gate Networks for Video Copy Detection

arXiv:2604.21694v1 Announce Type: cross Abstract: Video copy detection requires robust similarity estimation under diverse visual distortions while operating at very large scale. Although deep neural

Encoder-Free Human Motion Understanding via Structured Motion Descriptions

arXiv:2604.21668v1 Announce Type: new Abstract: The world knowledge and reasoning capabilities of text-based large language models (LLMs) are advancing rapidly, yet current approaches to human motion

safetyarxiv-cs-cv

EngramaBench: Evaluating Long-Term Conversational Memory with Structured Graph Retrieval

arXiv:2604.21229v1 Announce Type: cross Abstract: Large language model assistants are increasingly expected to retain and reason over information accumulated across many sessions. We introduce Engrama

Entropy Ratio Clipping as a Soft Global Constraint for Stable Reinforcement Learning

arXiv:2512.05591v2 Announce Type: replace-cross Abstract: Large language model post-training relies on reinforcement learning to improve model capability and alignment quality. However, the off-policy

safetyarxiv-cs-cl

Fairness Evaluation and Inference Level Mitigation in LLMs

arXiv:2510.18914v4 Announce Type: replace-cross Abstract: Large language models often display undesirable behaviors embedded in their internal representations, undermining fairness, inconsistency drif

safetyarxiv-cs-ai

Fake or Real, Can Robots Tell? Evaluating VLM Robustness to Domain Shift in Single-View Robotic Scene Understanding

arXiv:2506.19579v3 Announce Type: replace-cross Abstract: Robotic scene understanding increasingly relies on Vision-Language Models (VLMs) to generate natural language descriptions of the environment.

Geo-R1: Improving Few-Shot Geospatial Referring Expression Understanding with Reinforcement Fine-Tuning

arXiv:2509.21976v3 Announce Type: replace-cross Abstract: Referring expression understanding in remote sensing poses unique challenges, as it requires reasoning over complex object-context relationshi

Grounding Video Reasoning in Physical Signals

arXiv:2604.21873v1 Announce Type: new Abstract: Physical video understanding requires more than naming an event correctly. A model can answer a question about pouring, sliding, or collision from textu

GS-Quant: Granular Semantic and Generative Structural Quantization for Knowledge Graph Completion

arXiv:2604.21649v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown immense potential in Knowledge Graph Completion (KGC), yet bridging the modality gap between continuous graph em

HWE-Bench: Benchmarking LLM Agents on Real-World Hardware Bug Repair Tasks

arXiv:2604.14709v2 Announce Type: replace Abstract: Existing benchmarks for hardware design primarily evaluate Large Language Models (LLMs) on isolated, component-level tasks such as generating HDL mo

Improving Performance in Classification Tasks with LCEN and the Weighted Focal Differentiable MCC Loss

arXiv:2604.21252v1 Announce Type: new Abstract: The LASSO-Clip-EN (LCEN) algorithm was previously introduced for nonlinear, interpretable feature selection and machine learning. However, its design an

researcharxiv-cs-lg

It's High Time: A Survey of Temporal Question Answering

arXiv:2505.20243v4 Announce Type: replace Abstract: Time plays a critical role in how information is generated, retrieved, and interpreted. In this survey, we provide a comprehensive overview of Tempo

KD-CVG: A Knowledge-Driven Approach for Creative Video Generation

arXiv:2604.21362v1 Announce Type: new Abstract: Creative Generation (CG) leverages generative models to automatically produce advertising content that highlights product features, and it has been a si

safetyarxiv-cs-cv

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems

arXiv:2508.10177v3 Announce Type: replace Abstract: Recent Large Language Model (LLM)-based AutoML systems demonstrate impressive capabilities but face significant limitations such as constrained expl

Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems

arXiv:2604.21794v1 Announce Type: new Abstract: Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and or

Locating acts of mechanistic reasoning in student team conversations with mechanistic machine learning

arXiv:2604.21870v1 Announce Type: cross Abstract: STEM education researchers are often interested in identifying moments of students' mechanistic reasoning for deeper analysis, but have limited capaci

safetyarxiv-cs-lg

Machine learning and digital pragmatics: Which word category influences emoji use most?

arXiv:2604.21108v1 Announce Type: new Abstract: This study investigates Machine Learning (ML) in the prediction of emojis in Arabic tweets employing the (state-of-the-art) MARBERT model. A corpus of 1

researcharxiv-cs-cl

MATRAG: Multi-Agent Transparent Retrieval-Augmented Generation for Explainable Recommendations

arXiv:2604.20848v1 Announce Type: cross Abstract: Large Language Model (LLM)-based recommendation systems have demonstrated remarkable capabilities in understanding user preferences and generating per

MCAP: Deployment-Time Layer Profiling for Memory-Constrained LLM Inference

model-releasesarxiv-cs-lg

arXiv:2604.21026v1 Announce Type: new Abstract: Deploying large language models to heterogeneous hardware is often constrained by memory, not compute. We introduce MCAP (Monte Carlo Activation Profili

Agents

OpInf-LLM: Parametric PDE Solving with LLMs via Operator Inference

arXiv:2602.01493v2 Announce Type: replace-cross Abstract: Solving diverse partial differential equations (PDEs) is fundamental in science and engineering. Large language models (LLMs) have demonstrate

agentsarxiv-cs-ai

RailVQA: A Benchmark and Framework for Efficient Interpretable Visual Cognition in Automatic Train Operation

arXiv:2603.27112v2 Announce Type: replace Abstract: As Automatic Train Operation (ATO) advances toward GoA4 and beyond, it increasingly depends on efficient, reliable cab-view visual perception and de

Reinforcing 3D Understanding in Point-VLMs via Geometric Reward Credit Assignment

arXiv:2604.21160v1 Announce Type: new Abstract: Point-Vision-Language Models promise to empower embodied agents with executable spatial reasoning, yet they frequently succumb to geometric hallucinatio

Reversible Deep Learning for 13C NMR in Chemoinformatics: On Structures and Spectra

arXiv:2602.03875v4 Announce Type: replace-cross Abstract: We introduce a reversible deep learning model for 13C NMR that uses a single conditional invertible neural network for both directions between

Robust Test-time Video-Text Retrieval: Benchmarking and Adapting for Query Shifts

arXiv:2604.20851v1 Announce Type: cross Abstract: Modern video-text retrieval (VTR) models excel on in-distribution benchmarks but are highly vulnerable to real-world query shifts, where the distribut

SlideAgent: Hierarchical Agentic Framework for Multi-Page Visual Document Understanding

arXiv:2510.26615v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external knowledge, but it must balance limited effective context, re

Symbolic Grounding Reveals Representational Bottlenecks in Abstract Visual Reasoning

arXiv:2604.21346v1 Announce Type: new Abstract: Vision--language models (VLMs) often fail on abstract visual reasoning benchmarks such as Bongard problems, raising the question of whether the main bot

Local Ai

Teacher-Guided Routing for Sparse Vision Mixture-of-Experts

arXiv:2604.21330v1 Announce Type: new Abstract: Recent progress in deep learning has been driven by increasingly large-scale models, but the resulting computational cost has become a critical bottlene

local-aiarxiv-cs-cv

The Path Not Taken: Duality in Reasoning about Program Execution

arXiv:2604.20917v1 Announce Type: cross Abstract: Large language models (LLMs) have shown remarkable capabilities across diverse coding tasks. However, their adoption requires a true understanding of

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting

arXiv:2511.18539v2 Announce Type: replace-cross Abstract: We propose TimePre, a simple framework that unifies the efficiency of Multilayer Perceptron (MLP)-based models with the distributional flexibi

Unsupervised Learning of Inter-Object Relationships via Group Homomorphism

arXiv:2604.20925v1 Announce Type: new Abstract: While current deep learning models achieve high performance by learning statistical correlations from vast datasets,which stands in stark contrast to hu

researcharxiv-cs-lg

Validating a Deep Learning Algorithm to Identify Patients with Glaucoma using Systemic Electronic Health Records

arXiv:2604.20921v1 Announce Type: new Abstract: We evaluated whether a glaucoma risk assessment (GRA) model trained on All of Us national data can identify patients at high probability of glaucoma usi

researcharxiv-cs-lg

VidHal: Benchmarking Temporal Hallucinations in Vision LLMs

arXiv:2411.16771v3 Announce Type: replace Abstract: Vision Large Language Models (VLLMs) are widely acknowledged to be prone to hallucinations. Existing research addressing this problem has primarily

Weighting What Matters: Boosting Sample Efficiency in Medical Report Generation via Token Reweighting

arXiv:2604.21082v1 Announce Type: new Abstract: Training vision-language models (VLMs) for medical report generation is often hindered by the scarcity of high-quality annotated data. This work evaluat

researcharxiv-cs-cl

ActuBench: A Multi-Agent LLM Pipeline for Generation and Evaluation of Actuarial Reasoning Tasks

arXiv:2604.20273v1 Announce Type: new Abstract: We present ActuBench, a multi-agent LLM pipeline for the automated generation and evaluation of advanced actuarial assessment items aligned with the Int

23 Apr 2026

Anchor-and-Resume Concession Under Dynamic Pricing for LLM-Augmented Freight Negotiation

arXiv:2604.20732v1 Announce Type: cross Abstract: Freight brokerages negotiate thousands of carrier rates daily under dynamic pricing conditions where models frequently revise targets mid-conversation

23 Apr 2026

ATIR: Towards Audio-Text Interleaved Contextual Retrieval

arXiv:2604.20267v1 Announce Type: cross Abstract: Audio carries richer information than text, including emotion, speaker traits, and environmental context, while also enabling lower-latency processing