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REFINE: A Multi-Agent LLM Approach for Evidence-Guided Code Refactoring

arXiv:2608.23611v1 Announce Type: cross Abstract: Large Language Models (LLMs) offer new opportunities for automated code refactoring. However, generated changes must reduce targeted quality problems

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Research

ReGround-Surg: Reliability-Guided Anchor Grounding for Referring Surgical Video Segmentation

DGX agent

arXiv:2608.24671v1 Announce Type: new Abstract: Referring surgical video segmentation requires segmenting a target instrument or tissue region across video frames according to a natural language expre

researcharxiv-cs-cv

26 Aug 2026

Retrieval-augmented generation vs. deterministic tax computation in multi-agent financial advisory: A 2x2 factorial experiment

arXiv:2608.23908v1 Announce Type: new Abstract: Tax-loss harvesting demonstrates consistent benefits to long-term portfolio growth; yet implementing it efficiently often involves complex consideration

SAGE: From Direct Answering to Evidence-Grounded Inference for Chinese Ancient Document Understanding

arXiv:2608.24011v1 Announce Type: cross Abstract: Chinese ancient document understanding demands complex visual, linguistic, and historical reasoning. Current Large Vision-Language Models (LVLMs) typi

TLXML: Task-Level Explanation of Meta-Learning via Influence Functions

arXiv:2501.14271v4 Announce Type: replace Abstract: Meta-learning enables models to rapidly adapt to new tasks by leveraging prior experience, but its adaptation mechanisms remain opaque, especially r

researcharxiv-cs-lg

When Do Supervised UQ Ensembles Improve LLM Hallucination Detection? A Robustness Study

arXiv:2608.24492v1 Announce Type: cross Abstract: Uncertainty quantification (UQ) methods are widely used for hallucination detection in large language models (LLMs) in closed-book settings where grou

researcharxiv-cs-ai

AcroMELD: Recovering Interactive PDF Forms with Structure-Aware Graph Set Transformers

model-releasesarxiv-cs-cv

arXiv:2608.22338v1 Announce Type: new Abstract: Interactive PDF form fields are often absent from documents that visually resemble forms, leaving users unable to enter data without printing or externa

Adaptive Multilevel Twisted Sequential Monte Carlo for Rare Events Estimation in Language Models

arXiv:2608.21736v1 Announce Type: new Abstract: Rare unsafe behaviors in large language models can remain practically significant even when their probability is extremely small, particularly at deploy

safetyarxiv-cs-lg

Addressing the Selection Problem in Explainable AI

arXiv:2608.22356v1 Announce Type: new Abstract: Explainable AI (XAI) research has produced a plethora of explanation techniques, yet user studies repeatedly show that available explanations are not ef

An end-to-end-trained vision-language model for native-language prostate pathology report generation

arXiv:2608.23143v1 Announce Type: new Abstract: Prostate cancer is among the most frequently diagnosed malignancies worldwide, and structured reporting of each biopsy core burdens pathologists. Existi

local-aiarxiv-cs-cv

Apodex 1.1: Scaling Agentic Intelligence for Complex Work

arXiv:2608.23283v1 Announce Type: new Abstract: General-purpose language models can reason and synthesize knowledge, but complex work also requires sustained interaction with files, information source

AutoSaddler: Automatic Harness Optimization with Durable Updates from Agent Execution Traces

arXiv:2608.23041v1 Announce Type: new Abstract: LLM agents remain unreliable on long-horizon tasks, where small local failures can compound over extended interactions and lead to overall task failure.

Beyond Benchmarks: LLM Evaluation with an Anthropomorphic and Lifecycle-oriented Roadmap

arXiv:2508.18646v3 Announce Type: replace Abstract: Despite their rapid advancement, large language models (LLMs) suffer from a critical disconnect between benchmark scores and real-world utility. Cur

CAIA in Practice: Field Evaluation of an AI-Assisted Support System for Text-Based Online Counselling

arXiv:2608.22251v1 Announce Type: cross Abstract: Rising global demand for mental health support creates significant service delivery challenges, with asynchronous email counselling serving as a cruci

safetyarxiv-cs-cl

CallScreenBench: Benchmarking Small Language Models as Phone Secretaries

arXiv:2608.01033v2 Announce Type: replace-cross Abstract: Language models small enough to run on a handset, quantized to a few bits, are increasingly capable of acting on their user's behalf -- which

ClawProBench: Trace-Aware Evaluation of AI Agents with Runtime Coverage and Frozen Workplace-Style Holdouts

arXiv:2608.22510v1 Announce Type: new Abstract: Agent benchmarks often evaluate only final answers even when agents run on stateful runtimes. We argue this under-specifies what is being evaluated: the

Constructing Predictive Surgical Path for AI-based Capsulorhexis Skill Transfer

arXiv:2608.21441v1 Announce Type: cross Abstract: Automated training of surgeons is one of the most crucial factors that significantly minimize surgical training risks and expenses. With recent advanc

Context as an Environment: Programmatic Context Management for Long-Horizon Agents

arXiv:2608.21690v1 Announce Type: new Abstract: LLM agents increasingly take on long-running tasks whose history grows far beyond a single model context window. Existing approaches compress earlier in

CONTRAMEM: Learning Self-Evolving Procedural Memory from Contrasting Multi-Model Trajectories

arXiv:2608.22533v1 Announce Type: new Abstract: Autonomous computer-use agents are increasingly applied to long-horizon tasks requiring coordinated application calls, persistent state tracking, and ve

CyberFactory: Scaling Cyber Security Capabilities with Instances from the Wild

arXiv:2608.23181v1 Announce Type: cross Abstract: As large language models (LLMs) continue to advance in coding capabilities, their potential in cybersecurity has drawn increasing research attention,

CyrillicQA: The Influence of Phonetically Encoded Secret Language on LLM Performance

arXiv:2608.21462v1 Announce Type: cross Abstract: Due to the selection of their training data, large language models (LLMs) perform best on standard-language inputs from languages using the Latin alph

researcharxiv-cs-ai

DIGing--SGLD: Decentralized and Scalable Langevin Sampling over Time--Varying Networks

arXiv:2511.12836v2 Announce Type: replace-cross Abstract: Sampling from a target distribution induced by training data is central to Bayesian learning, with Stochastic Gradient Langevin Dynamics (SGLD

safetyarxiv-cs-lg

Gated Decoupled Compositional Bandits: A Unified Theory of Contextual Bandits with Supervised-Calibrated Action Scaling and Pre-Execution Gating

arXiv:2608.21993v1 Announce Type: new Abstract: We introduce Gated Decoupled Compositional Bandits (GDCB), a family of contextual bandit algorithms with three structural innovations that jointly fall

Grounding Isn't Knowing: Do VLMs Need Object Localization for Spatial Reasoning?

arXiv:2608.23074v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer spatial questions, yet the mechanisms connecting object grounding to spatial reasoning remain poorly understood

local-aiarxiv-cs-cv

Interpretable AI with Local Distillation

arXiv:2608.23538v1 Announce Type: cross Abstract: Modern AI models such as tabular foundation models and gradient-boosted ensembles can outpredict classical methods, but provide little basis for reaso

KMGen: A Skill-based Approach for Synthetic Individual Patient Data Generation

arXiv:2608.22618v1 Announce Type: new Abstract: Individual patient data (IPD) from clinical trials is the substrate for survival modeling, meta-analysis, and safety research, yet IPD is rarely release

KPI-Conditioned Generative Design of Automotive Hood Inner Panels: A Two-Stage Retrieval-Generation Pipeline with Surrogate-Based Performance Estimation

arXiv:2608.22457v1 Announce Type: new Abstract: An inner hood panel must meet a deflection target, stay below a stress limit, and hit a mass target. Machine-learned surrogates have made the forward di

researcharxiv-cs-lg

LLM assisted writing deserves empirical evaluation

arXiv:2608.22124v1 Announce Type: new Abstract: LLM-assisted writing is often treated as a detection problem, as it raises questions about clarity, integrity, equity, and evaluation. An analysis of 69

agentsarxiv-cs-cl

LLMs for Survey Text Analysis - A Performance Comparison Between Humans and GPT-5 on Inductive Content Analysis

arXiv:2608.22417v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to support text analysis in qualitative research, yet evidence on their performance in inductive cont

Ludi{}_{scriptscriptstyle 0.1}: An Agentic System for Socially Intelligent Robots

arXiv:2608.22035v1 Announce Type: new Abstract: Robot foundation models have substantially advanced perception and control, but natural human-robot collaboration requires more than executing isolated

agentsarxiv-cs-ro

MADE: Benchmark Environments for Closed-Loop Materials Discovery

arXiv:2601.20996v2 Announce Type: replace Abstract: Existing benchmarks for computational materials discovery primarily evaluate static predictive tasks or isolated computational sub-tasks. While valu

MediSkill-Evo: Process-Constrained Self-Evolution for Evidence-Grounded Clinical Interaction

arXiv:2608.23397v1 Announce Type: new Abstract: Interactive clinical agents must gather decisive evidence and convert it into grounded actions under partial observability. A correct final diagnosis al

Mining Artifacts in Mycelium SEM Micrographs

arXiv:2103.07573v2 Announce Type: replace-cross Abstract: Mycelium is a promising biomaterial based on fungal mycelium, a highly porous, nanofibrous structure. Scanning electron micrographs are used t

researcharxiv-cs-cv

Mitigating Explanation Leakage in Financial Fraud Detection Systems

arXiv:2608.22607v1 Announce Type: new Abstract: Financial fraud detection relies heavily on centralized machine learning models. This creates serious data privacy risks. Federated Learning (FL) decent

researcharxiv-cs-lg

Neural Boltzmann Equations

arXiv:2608.23022v1 Announce Type: cross Abstract: The dynamics of particles in the early universe are described by Boltzmann equations, which involve high-dimensional phase-space integrals. Classical

Opportunities and Challenges of Natural Language Processing for Low-Resource Senegalese Languages in Social Science Research

arXiv:2601.09716v2 Announce Type: replace Abstract: Natural Language Processing (NLP) is rapidly transforming research methodologies across disciplines, yet African languages remain largely underrepre

researcharxiv-cs-cl

PersonaMem-v3: Toward Omni-Platform Personal Intelligence for Holistic User Understanding, Recommendation, and Agentic Tasks

arXiv:2608.21381v1 Announce Type: cross Abstract: Personal intelligence is becoming a central frontier for user-facing AI agents. To be helpful in everyday life, agents must understand users across th

RAG Collapse: LLM Responses Collapse When Retrieved Documents Are Self-Authored

arXiv:2608.22118v1 Announce Type: new Abstract: LLM responses are based on the internet (via training or RAG), and AI is now used to generate a significant amount of content online (Paredes et al., 20

safetyarxiv-cs-cl

RIACT: A Responsible AI System for Personalized Study Habit Tracking and Early Burnout Signal Detection in University Students

arXiv:2608.21379v1 Announce Type: new Abstract: Student burnout is highly prevalent in higher education, with reported rates ranging from 12% to over 70% and consistently exceeding those of the workin

safetyarxiv-cs-ai

Applications

RoboShape: Information-Theoretic Point Cloud Representations for Privacy-Aware Robot Perception

arXiv:2608.21380v1 Announce Type: cross Abstract: With the increased adoption of robotic agents operating in human environments by scanning and sharing 3D representations (e.g., for fleet learning, cl

applicationsarxiv-cs-ai

Safety Training May Persist Through Helpfulness Optimization in LLM Agents

arXiv:2603.02229v2 Announce Type: replace-cross Abstract: Safety post-training has been studied extensively in single-step 'chat' settings where safety typically refers to refusing harmful requests. W

SAGE: Stability-Aware Graph-Based Ensemble Feature Selection for Explainable Postpartum Depression Risk Prediction

arXiv:2608.22809v1 Announce Type: new Abstract: Postpartum depression (PPD) poses a major burden on maternal and child health, especially in low- and middle-income countries where prevalence exceeds 1

local-aiarxiv-cs-lg

SAS: Segment Anything Small for Ultrasound -- A Non-Generative Data Augmentation Technique for Robust Deep Learning in Ultrasound Imaging

arXiv:2503.05916v2 Announce Type: replace-cross Abstract: Accurate segmentation of anatomical structures in ultrasound (US) images, particularly small ones, is challenging due to noise and variability

researcharxiv-cs-ai

SecOPD: Mitigating Adaptive Prompt Injections by On-Policy Distillation

arXiv:2608.21500v1 Announce Type: cross Abstract: Prompt injection is listed as the #1 threat to AI agents. When an agent accesses external data from websites, files, or emails, an attacker may inject

safetyarxiv-cs-ai

Hardware

Self-Calibrating Dense Displacement Fields for Reliable Co-Registration of Large Optical Satellite Imagery

arXiv:2608.22300v1 Announce Type: new Abstract: Co-registration underlies nearly every multi-temporal and multi-sensor use of optical satellite imagery, and operational products still carry documented

hardwarearxiv-cs-cv

Signal or Noise? A Benchmark Study of Agent Skills in Web Development

arXiv:2608.23067v1 Announce Type: new Abstract: Agent Skills are reusable procedural modules that are increasingly injected into coding-agent sessions to encode framework conventions, anti-patterns, a

Small Reasoning Models are Instruction Followers in Function Calling

arXiv:2608.22472v1 Announce Type: new Abstract: Function calling represents the core capability of agentic large language models (LLMs). Existing research has focused on enhancing LLMs function-callin

local-aiarxiv-cs-ai

Structured Learning on Mapper Representations

arXiv:2608.22044v1 Announce Type: cross Abstract: Modern machine learning (ML) methods are highly effective for prediction tasks, but many commonly used representations reduce complex data to fixed di