Search: “models”

Latency-Quality Routing for Functionally Equivalent Tools in LLM Agents

arXiv:2605.14241v1 Announce Type: new Abstract: Tool-augmented LLM agents increasingly access the same tool type through multiple functionally equivalent providers, such as web-search APIs, retrievers

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Learning from Failures: Correction-Oriented Policy Optimization with Verifiable Rewards

DGX agent

arXiv:2605.14539v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as an effective paradigm for improving the reasoning capabilities of large language mo

safetyarxiv-cs-cl

15 May 2026

LoRIF: Low-Rank Influence Functions for Scalable Training Data Attribution

arXiv:2601.21929v2 Announce Type: replace Abstract: Training data attribution (TDA) identifies which training examples most influenced a model's prediction. Influence function methods are a theoretica

researcharxiv-cs-lg

LoVeC: Reinforcement Learning for Better Verbalized Confidence in Long-Form Generations

arXiv:2505.23912v2 Announce Type: replace-cross Abstract: Hallucination remains a major challenge for the safe and trustworthy deployment of large language models (LLMs) in factual content generation.

MahaVar: OOD Detection via Class-wise Mahalanobis Distance Variance under Neural Collapse

arXiv:2605.14413v1 Announce Type: cross Abstract: Out-of-distribution (OOD) detection is a critical component for ensuring the reliability of deep neural networks in safety-critical applications. In t

MD-PNOP: Equation-Recast Neural Operators for Minimal-Data Extrapolation and PDE Solver Acceleration

arXiv:2509.01416v2 Announce Type: replace Abstract: The computational overhead of traditional numerical solvers for partial differential equations (PDEs) remains a critical bottleneck for large-scale

MemEye: A Visual-Centric Evaluation Framework for Multimodal Agent Memory

arXiv:2605.15128v1 Announce Type: cross Abstract: Long-term agent memory is increasingly multimodal, yet existing evaluations rarely test whether agents preserve the visual evidence needed for later r

Mixed Integer Goal Programming for Personalized Meal Optimization with User-Defined Serving Granularity

arXiv:2605.13849v1 Announce Type: new Abstract: Determining what to eat to satisfy nutritional requirements is one of the oldest optimization problems in operations research, yet existing formulations

MoRe: Modular Representations for Principled Continual Representation Learning on Squantial Data

arXiv:2605.14364v1 Announce Type: new Abstract: Continual learning requires models to adapt to new data while preserving previously acquired knowledge. At its core, this challenge can be viewed as pri

safetyarxiv-cs-lg

Multi-Scale Dequant: Eliminating Dequantization Bottleneck via Activation Decomposition for Efficient LLM Inference

arXiv:2605.13915v1 Announce Type: cross Abstract: Quantization is essential for efficient large language model (LLM) inference, yet the dequantization step-converting low-bit weights back to high-prec

Multimodal Causal-Driven Representation Learning for Generalizable Medical Image Segmentation

arXiv:2508.05008v2 Announce Type: replace Abstract: Vision-Language Models (VLMs), such as CLIP, have demonstrated remarkable zero-shot capabilities in various computer vision tasks. However, their ap

researcharxiv-cs-cv

Near-Miss: Latent Policy Failure Detection in Agentic Workflows

arXiv:2603.29665v2 Announce Type: replace Abstract: Agentic systems for business process automation often require compliance with policies governing conditional updates to the system state. Evaluation

Network-Aware Bilinear Tokenization for Brain Functional Connectivity Representation Learning

arXiv:2605.14048v1 Announce Type: new Abstract: Masked autoencoders (MAEs) have recently shown promise for self-supervised representation learning of resting-state brain functional connectivity (FC).

Novel Dynamic Batch-Sensitive Adam Optimiser for Vehicular Accident Injury Severity Prediction

arXiv:2605.15083v1 Announce Type: cross Abstract: The choice of optimiser is important in deep learning, as it strongly influences model efficiency and speed of convergence. However, many commonly use

Performance Guarantees for Quantum Neural Estimation of Entropies

arXiv:2511.19289v2 Announce Type: replace-cross Abstract: Estimating quantum entropies and divergences is an important problem in quantum physics, information theory, and machine learning. Quantum neu

Physics-R1: An Audited Olympiad Corpus and Recipe for Visual Physics Reasoning

arXiv:2605.14040v1 Announce Type: new Abstract: We audit the multimodal-physics evaluation pipeline end-to-end and document three undetected construction practices that distort how the field measures

Prompting Policies for Multi-step Reasoning and Tool-Use in Black-box LLMs with Iterative Distillation of Experience

arXiv:2605.14443v1 Announce Type: new Abstract: The shift toward interacting with frozen, 'black-box' Large Language Models (LLMs) has transformed prompt engineering from a heuristic exercise into a c

PROVE: A Perceptual RemOVal cohErence Benchmark for Visual Media

arXiv:2605.14534v1 Announce Type: cross Abstract: Evaluating object removal in images and videos remains challenging because the task is inherently one-to-many, yet existing metrics frequently disagre

QOuLiPo: What a quantum computer sees when it reads a book

arXiv:2605.14188v1 Announce Type: cross Abstract: What does a book look like to a quantum computer? This paper takes eight classical works of the Renaissance and its late-antique inheritance -- from A

Quantifying and Mitigating Premature Closure in Frontier LLMs

arXiv:2605.15000v1 Announce Type: cross Abstract: Premature closure, or committing to a conclusion before sufficient information is available, is a recognized contributor to diagnostic error but remai

RAM-W600: A Multi-Task Wrist Dataset and Benchmark for Rheumatoid Arthritis

arXiv:2507.05193v4 Announce Type: replace-cross Abstract: Rheumatoid arthritis (RA) is a common autoimmune disease that has been the focus of research in computer-aided diagnosis (CAD) and disease mon

RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling

arXiv:2510.20206v2 Announce Type: replace Abstract: Prompt design plays a crucial role in text-to-video (T2V) generation, yet user-provided prompts are often short, unstructured, and misaligned with t

safetyarxiv-cs-cv

Real-time virtual circuits for plasma shape control via neural network emulators

arXiv:2605.14939v1 Announce Type: cross Abstract: Reliable position and shape control in tokamak plasmas requires accurate real-time regulation of several strongly coupled shape parameters. The contro

Real2Sim in HOI: Toward Physically Plausible HOI Reconstruction from Monocular Videos

arXiv:2605.14462v1 Announce Type: new Abstract: Recovering 4D human-object interaction (HOI) from monocular video is a key step toward scalable 3D content creation, embodied AI, and simulation-based l

Reinforcement Learning with Semantic Rewards Enables Low-Resource Language Expansion without Alignment Tax

arXiv:2605.14366v1 Announce Type: new Abstract: Extending large language models (LLMs) to low-resource languages often incurs an 'alignment tax': improvements in the target language come at the cost o

safetyarxiv-cs-cl

Residual Stream Duality in Modern Transformer Architectures

arXiv:2603.16039v2 Announce Type: replace-cross Abstract: Recent work has made clear that the residual pathway is not mere optimization plumbing; it is part of the model's representational machinery.

SceneParser: Hierarchical Scene Parsing for Visual Semantics Understanding

arXiv:2605.14923v1 Announce Type: new Abstract: General scene perception has progressed from object recognition toward open-vocabulary grounding, part localization, and affordance prediction. Yet thes

Sheaf-Theoretic Transport and Obstruction for Detecting Scientific Theory Shift in AI Agents

arXiv:2605.14033v1 Announce Type: new Abstract: Scientific theory shift in AI agents requires more than fitting equations to data. An artificial scientific agent must detect whether an existing repres

SPIN: Structural LLM Planning via Iterative Navigation for Industrial Tasks

arXiv:2605.14051v1 Announce Type: new Abstract: Industrial LLM agent systems often separate planning from execution, yet LLM planners frequently produce structurally invalid or unnecessarily long work

SR-Prominence: A Crowdsourced Protocol and Dataset Suite for Perceptually-Weighted Super-Resolution Artifact Evaluation

arXiv:2605.14847v1 Announce Type: new Abstract: Modern image super-resolution methods generate detailed, visually appealing results, but they often introduce visual artifacts: unnatural patterns and t

Local Ai

SteerSeg: Attention Steering for Reasoning Video Segmentation

arXiv:2605.14908v1 Announce Type: new Abstract: Video reasoning segmentation requires localizing objects across video frames from natural language expressions, often involving spatial reasoning and im

local-aiarxiv-cs-cv

Agents

Stochastic dynamics learning with state-space systems

arXiv:2508.07876v2 Announce Type: replace-cross Abstract: This work advances the theoretical foundations of reservoir computing (RC) by providing a unified treatment of fading memory and the echo stat

agentsarxiv-cs-lg

TERMINATOR: Learning Optimal Exit Points for Early Stopping in Chain-of-Thought Reasoning

arXiv:2603.12529v2 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs) achieve impressive performance on complex reasoning tasks via Chain-of-Thought (CoT) reasoning, which enables th

TERRA-CD: Multi-Temporal Framework for Multi-class and Semantic Change Detection

arXiv:2605.14651v1 Announce Type: new Abstract: Urban vegetation monitoring plays a vital role in understanding environmental changes, yet comprehensive datasets for this purpose remain limited. To ad

The Evaluation Trap: Benchmark Design as Theoretical Commitment

arXiv:2605.14167v1 Announce Type: new Abstract: Every AI benchmark operationalizes theoretical assumptions about the capability it claims to assess. When assumptions function as unexamined commitments

The Moltbook Observatory Archive: an incremental dataset of agent-only social network activity

arXiv:2605.13860v1 Announce Type: cross Abstract: Moltbook is a social media platform in which posts and comments are authored exclusively by autonomous AI agents. We present the Moltbook Observatory

TILBench: A Systematic Benchmark for Tabular Imbalanced Learning Across Data Regimes

arXiv:2605.14915v1 Announce Type: new Abstract: Imbalanced learning remains a fundamental challenge in tabular data applications. Despite decades of research and numerous proposed algorithms, a system

TILT: Target-induced loss tilting under covariate shift

arXiv:2605.14280v1 Announce Type: new Abstract: We introduce and analyze Target-Induced Loss Tilting (TILT) for unsupervised domain adaptation under covariate shift. It is based on a novel objective f

ToMAToMP: Robust and Multi-Parameter Topological Clustering

arXiv:2605.14824v1 Announce Type: new Abstract: Topological clustering, and its main algorithm ToMATo, is a clustering method from Topological Data Analysis (TDA) which has been applied successfully i

Hardware

Towards Resource-Efficient LLMs: End-to-End Energy Accounting of Distillation Pipelines

arXiv:2605.13981v1 Announce Type: cross Abstract: The rise in deployment of large language models has driven a surge in GPU demand and datacenter scaling, raising concerns about electricity use, grid

hardwarearxiv-cs-ai

Understanding How International Students in the U.S. Are Using Conversational AI to Support Cross-Cultural Adaptation

arXiv:2605.15127v1 Announce Type: cross Abstract: Moving to a new culture and adapting to a new life, as an international student, can be a stressful experience. In the US, international students face

V2M-Zero: Zero-Pair Time-Aligned Video-to-Music Generation

arXiv:2603.11042v2 Announce Type: replace-cross Abstract: Generating music that temporally aligns with video events is challenging for existing text-to-music models, which lack fine-grained temporal c

VGGT-360: Geometry-Consistent Zero-Shot Panoramic Depth Estimation

arXiv:2603.18943v2 Announce Type: replace Abstract: This paper presents VGGT-360, a novel training-free framework for zero-shot, geometry-consistent panoramic depth estimation. Unlike prior view-indep

researcharxiv-cs-cv

Vision-Based Runtime Monitoring under Varying Specifications using Semantic Latent Representations

arXiv:2605.13923v1 Announce Type: cross Abstract: We study certified runtime monitoring of past-time signal temporal logic (ptSTL) from visual observations under partial observability. The monitor mus

Watermarking Game-Playing Agents in Perfect-Information Extensive-Form Games

arXiv:2605.14283v1 Announce Type: cross Abstract: Watermarking techniques for large language models (LLMs), which encode hidden information in the output so its source can be verified, have gained sig

When Answers Stray from Questions: Hallucination Detection via Question-Answer Orthogonal Decomposition

arXiv:2605.14449v1 Announce Type: cross Abstract: Hallucination detection in large language models (LLMs) requires balancing accu racy, efficiency, and robustness to distribution shift. Black-box cons

When Are Two Networks the Same? Tensor Similarity for Mechanistic Interpretability

arXiv:2605.15183v1 Announce Type: new Abstract: Mechanistic interpretability aims to break models into meaningful parts; verifying that two such parts implement the same computation is a prerequisite.

researcharxiv-cs-lg

XAI and Statistical Analysis for Reliable Intrusion Detection in the UAVIDS-2025 Dataset: From Tree to Hybrid and Tabular DNN Ensembles

arXiv:2605.13922v1 Announce Type: cross Abstract: During the last few years, the term Mechanistic Interpretability, a specific area, under the umbrella of explainable artificial intelligence (XAI), ha

researcharxiv-cs-lg