Search: “models”

SkillForge: Self-Distilling Agents for Project-Specific Issue Resolution

arXiv:2608.18933v1 Announce Type: cross Abstract: Large language model (LLM) based agents have demonstrated remarkable proficiency in automated software issue resolution, yet they often struggle to re

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StocksTalk: A Voice-Enabled Conversational Agent for Structured Query Generation over Web Data

DGX agent

arXiv:2608.18105v1 Announce Type: cross Abstract: StocksTalk is a voice-enabled conversational system for transforming spoken financial screening requests into executable and validated structured quer

model-releasesarxiv-cs-ai

20 Aug 2026

TrojanGYM: A Detector-in-the-Loop LLM for Adaptive RTL Hardware Trojan Insertion

arXiv:2601.17178v3 Announce Type: replace-cross Abstract: Hardware Trojans (HTs) remain a critical threat because learning-based detectors often overfit to narrow trigger/payload patterns and small, s

UMER: Unifying Embedding and Ranking via Pair-Aware Discriminative Reasoning for Universal Multimodal Retrieval

arXiv:2608.18504v1 Announce Type: new Abstract: Universal multimodal retrieval aims to support diverse instruction-aware retrieval tasks, demanding both efficient corpus-scale matching and fine-graine

Understanding Multilingual Medical ASR Adaptation Through Layer-Wise Analysis

arXiv:2608.18825v1 Announce Type: cross Abstract: Medical automatic speech recognition (MedASR) requires adaptation to specialised terminology, limited annotated clinical data, and multilingual use ca

What Makes Software Issue Resolution Tasks Difficult for Agents?

arXiv:2608.18280v1 Announce Type: cross Abstract: Background. Advances in agentic systems are simultaneously, and rapidly, saturating benchmarks. Despite this often discussed phenomena, benchmark scor

When Does Dynamic Ensembling Pay Off? Diagnosing Regionwise Gains in Regression under Distribution Shift

arXiv:2608.18330v1 Announce Type: new Abstract: Whether input-dependent ('dynamic') combination of a regression model pool beats the best static blend depends on the shift and is rarely known before d

researcharxiv-cs-lg

When Two Tracers Disagree: An Investigation of Multimodal Fusion for Clinical PET/CT Segmentation

arXiv:2608.19063v1 Announce Type: new Abstract: PSMA and FDG PET/CT visualise complementary biological information in prostate cancer. Combining both tracers could capture heterogeneous tumour phenoty

A Diffusion-Refined Planner with Reinforcement Learning Priors for Confined-Space Parking

arXiv:2510.14000v2 Announce Type: replace Abstract: The growing demand for parking has increased the need for automated parking planning methods that can operate reliably in confined spaces. In restri

safetyarxiv-cs-ro

An Investigation of the NeurIPS and ICML 2025 Position Tracks

model-releasesarxiv-cs-cl

arXiv:2608.16894v1 Announce Type: cross Abstract: ML venues shape what kinds of research claims become legible to reviewers and what forms of evidence count as rigorous. The NeurIPS and ICML Position

ArguLens: An Open-Source System for Automated Essay Scoring and Label-Aware Feedback Generation

model-releasesarxiv-cs-cl

arXiv:2608.17356v1 Announce Type: new Abstract: Most automated essay scoring (AES) systems output a single holistic score without interpretable evidence and rely on closed APIs that introduce data pri

Auditing Self-Evolution in Financial Agents: Capability Gains, Security Drift, and Execution-Interface Mismatch

arXiv:2608.17684v1 Announce Type: new Abstract: Self-evolving agents turn experience into reusable skills, workflows, or memories, but post-evolution accuracy alone does not show whether learned behav

Benchmarking Automated Security Patch Backporting: How Far Are We?

arXiv:2608.17671v1 Announce Type: cross Abstract: Automated security patch backporting is critical for mitigating N-day vulnerabilities. Recent tools report success rates above 80% on their respective

CABLE: Extending the Reach of Memory Retrieval via Complementary Antecedent-Based Linking and Expansion

model-releasesarxiv-cs-cl

arXiv:2608.17911v1 Announce Type: new Abstract: As LLM agents operate across structured workflows and sessions, preserving long-term history does not ensure that later contexts can recover relevant ev

Collective Counterfactual Planning: Coordination, Consent, and Verification under Representational Constraints

arXiv:2608.17932v1 Announce Type: cross Abstract: Groups routinely complete projects that no single member can plan, execute, or verify alone. We propose a formal model of this phenomenon, Collective

agentsarxiv-cs-ai

Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analyses

arXiv:2311.09614v5 Announce Type: replace-cross Abstract: This study addresses critical gaps in automated lymphoma segmentation from PET/CT images, focusing on issues often overlooked in existing lite

Deep Academic Survey: Stateful Agentic Closed-Loop Paradigm for Academic Survey Automation

arXiv:2608.18034v1 Announce Type: new Abstract: Academic surveys play a central role in organizing rapidly expanding scholarly literature, yet their construction requires extensive paper analysis, coh

Delegation Asymmetry in Agentic Recommender Systems: Measuring Two-Sided Receptivity in Online Dating

arXiv:2608.18058v1 Announce Type: new Abstract: Autonomous LLM agents that converse on a user's behalf are an emerging design pattern in matching platforms, yet their viability depends on a condition

agentsarxiv-cs-ai

Detecting and Discriminating Operator Misspecification in Hybrid PDE-Parameter Learning: a Reference-Free Instrument, with Discrimination Bounded In Sample

arXiv:2608.16925v1 Announce Type: new Abstract: We build an instrument that reads, from a single fit and with no oracle, whether the operator a hybrid PDE-parameter estimator postulates is wrong-and s

Efficient Dynamic Shielding for Parametric Safety Specifications

arXiv:2505.22104v2 Announce Type: replace Abstract: Shielding has emerged as a promising approach for ensuring safety of AI-controlled autonomous systems. The algorithmic goal is to compute a shield,

Embodied-Navigator: Point, Think, Memorize, and Align for Efficient Navigation

arXiv:2608.17512v1 Announce Type: new Abstract: Although Large Vision-Language Models (VLMs) have significantly advanced embodied navigation, their direct deployment remains challenging, as existing m

safetyarxiv-cs-ro

Eval4Sim: An Evaluation Framework for Persona Simulation

arXiv:2603.02876v2 Announce Type: replace Abstract: Large Language Model personas, explicit profiles specifying a user's attributes, preferences, and behavioural tendencies, are increasingly used to s

safetyarxiv-cs-cl

Exact Reformulation and Optimization for Direct Metric Optimization in Binary Imbalanced Classification

arXiv:2507.15240v2 Announce Type: replace Abstract: For classification with imbalanced class frequencies, i.e., imbalanced classification (IC), standard accuracy is known to be misleading as a perform

Explicit State Elicitation Is Not Enough: A Controlled Audit of Memory-Policy Classification

arXiv:2608.17247v1 Announce Type: new Abstract: Personalized agents must decide whether retrieved user memory should be used, ignored, updated, or queried before it affects a current task. We use this

Local Ai

FedPref: Federated Preference Learning for Structured Radiology Report Extraction

arXiv:2608.16971v1 Announce Type: new Abstract: Radiology reports describe findings and locations in free text, but downstream search and analysis require these relations in a fixed schema. Learning t

local-aiarxiv-cs-ai

FetchMan: Learning Visual Humanoid Loco-Manipulation Policies from Simulated Experiences

model-releasesarxiv-cs-ro

arXiv:2608.17027v1 Announce Type: new Abstract: Visual loco-manipulation policies that can generalize to novel scenes and objects have long been a goal of robotics research. However, today's data-hung

From Global Benchmarks to Local Evaluations: Benchmarking LLMs for the German Public Sector

arXiv:2608.17827v1 Announce Type: new Abstract: Public institutions face a persistent challenge in selecting LLMs suited to their specific context. Existing benchmarks, however, are of limited use as

researcharxiv-cs-cl

GSToken: Geometry-Structured Gaussian Tokens for Compact 3D Medical Image Representation

arXiv:2608.17425v1 Announce Type: new Abstract: Effective segmentation of multi-modal MRI is central to improving neural network accuracy in brain tumor recognition. Existing methods typically compres

How smoothing the affinity matrix affects neighborhood preservation in t-SNE

arXiv:2608.17190v1 Announce Type: cross Abstract: Dimensionality reduction methods are instrumental to visualize high-dimensional data, and t-SNE stands as one of the most widely used methods due to i

Initialization-Free Bundle Adjustment Revisited: A Controlled Experimental Study

arXiv:2608.18028v1 Announce Type: new Abstract: Initialization-free bundle adjustment (InitFree BA) aims to recover camera poses and scene structure directly from image observations, avoiding the geom

KernelArc: A Multi-Agent Framework for GPU Kernel Optimization

arXiv:2608.17071v1 Announce Type: new Abstract: We present KernelArc, a multi-agent framework for autonomous GPU kernel optimization across heterogeneous workloads. Strategy-specialized agents run in

Lymphocyte Mimicry Correction via Region-Level Tissue Reasoning and Unbalanced Optimal Transport

arXiv:2608.17151v1 Announce Type: new Abstract: Cell mimicry arises when different cell types appear morphologically similar. Human pathologists resolve this ambiguity using surrounding tissue context

MobileWorldSafety: Benchmarking GUI Agent Safety Against Environmental Injection Attacks in Android Apps

arXiv:2608.17659v1 Announce Type: cross Abstract: LLM-powered GUI agents that autonomously operate smartphones are rapidly transitioning from research prototypes to early real-world deployment. Howeve

MoE-ViE: Mixture of Experts Vision Encoder for Efficient Image and Video Understanding

arXiv:2608.17402v1 Announce Type: new Abstract: Vision encoders are a critical component of vision-language models, and scaling their capacity effectively improves performance. However, dense scaling

NeuroPath: Brain-Inspired Dual-Pathway Graph Convolutional Networks for Skeleton-Based Action Recognition

arXiv:2608.17487v1 Announce Type: new Abstract: Skeleton-based action recognition aims to recognize human actions from sequences of human joint coordinates. Most existing Spatial-Temporal Graph Convol

Online Generalized Sparse Regression: How Does Overparametrization Help?

arXiv:2608.17466v1 Announce Type: cross Abstract: Regularized sparse regression has been extensively studied in the offline setting, but online formulation remains relatively under-explored. This gap

Optimize Your Sampling: Tuned Diffusion Sampling with Bayesian Optimization

arXiv:2608.18040v1 Announce Type: cross Abstract: Sampling from a diffusion model typically requires many forward passes through a large neural network, making generation computationally expensive. Wh

OV3D-Bench: A Diagnostic Benchmark for Open-Vocabulary Monocular 3D Detection

arXiv:2608.17110v1 Announce Type: new Abstract: Open-vocabulary monocular 3D detectors report strong in-domain performance, but each evaluates under a different protocol, several rely on per-image cat

Parametric Knowledge in RAG-SFT for Domain-Specific Document Generation

arXiv:2603.23047v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) fine-tuning has shown substantial improvements over vanilla RAG, yet most studies target document questio

Picture the Epsilon: Pursuing Identity-Level Privacy Guarantees for Images

arXiv:2608.17147v1 Announce Type: cross Abstract: Image-to-image face generators are widely used, and visual dissimilarity between their outputs and source images is sometimes treated as evidence of p

PRISM: Precision and contact-rich Real-world Industrial Skill dataset with Multimodal sensing

model-releasesarxiv-cs-ro

arXiv:2608.17962v1 Announce Type: new Abstract: Recent progress in robotic learning has been fueled by large-scale datasets collected in everyday environments. However, most existing datasets emphasiz

PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training

arXiv:2602.13840v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed in personalized tasks involving sensitive, context-dependent information, where privacy

agentsarxiv-cs-cl

Procedural Content Metageneration via Program Search and Continual Abstraction Discovery

arXiv:2608.17947v1 Announce Type: new Abstract: Large language models can generate executable programs, which makes it possible to search directly over procedural content generators rather than indivi

QuantumNovelty: A Skill-Orchestrating Language Agent for Referee-Style Review and Patentability Screening of Quantum Papers and Patents

arXiv:2608.16900v1 Announce Type: cross Abstract: Language-model agents increasingly produce quantum-science results; we ask whether the same agentic paradigm can also scrutinize them in an auditable,

agentsarxiv-cs-ai

Reinforcing Consistency in Video MLLMs with Structured Rewards

arXiv:2604.01460v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have achieved remarkable progress in video understanding. However, seemingly plausible outputs often suffer

safetyarxiv-cs-cv

SemComp-Bench: Benchmarking Semantic Task Completion in Video Generation

arXiv:2608.17426v1 Announce Type: cross Abstract: We introduce Semantic Task Completion Video Generation, an outcome-oriented video generation task. Under this formulation, success requires both achie

Supporting Calibrated Reliance in Human-AI Collaboration: Different Strategies for Different Tasks

arXiv:2604.03237v2 Announce Type: replace-cross Abstract: As AI systems increasingly support human decision making, a central challenge is determining what information helps people recognize when to r

TraceSQL: Traceable Answerability Estimation for Reference-Free Text-to-SQL Verification

arXiv:2608.17795v1 Announce Type: new Abstract: Text-to-SQL systems are commonly evaluated using ground-truth SQL queries or reference execution results, but such supervision is unavailable at inferen

safetyarxiv-cs-cl