Search: “evaluation”

R4Tun: LLM-guided adaptive segmental tunnel lining segmentation in point clouds

arXiv:2609.11360v1 Announce Type: new Abstract: Automated inspection of segmental tunnel linings requires adaptive segmentation from 3D point clouds, yet expert-tuned pipelines often degrade when tunn

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ReGround: Grounding Reviewer Comments in Multimodal Evidence

DGX agent

arXiv:2609.11460v1 Announce Type: new Abstract: Reviewer comments naturally relate to specific parts of the reviewed paper, yet grounding these comments to the underlying evidence is difficult due to

researcharxiv-cs-cl

11 Sept 2026

RIDE: Relocalization-Informed Depth Estimation with 3D Gaussian Splatting

arXiv:2609.11079v1 Announce Type: new Abstract: Render--match--PnP relocalization establishes correspondences between query image pixels and 3D map points for camera pose recovery, but their potential

researcharxiv-cs-ro

Robust Multimodal Sentiment Analysis with Incomplete Modalities via Semantic-aware Completeness based Reconstruction

arXiv:2609.10950v1 Announce Type: new Abstract: Recent multimodal sentiment analysis studies increasingly adopt text-centric fusion approaches to exploit the rich sentiment information inherent in the

Agents

RobustSGPO: Search-Space Control for Agent Harness Evolution

arXiv:2609.09646v1 Announce Type: new Abstract: Semantic-gradient-based prompt optimization (SGPO) improves agent harnesses using execution feedback, but its local update rule leaves the choice of edi

agentsarxiv-cs-ai

Safety-aware Skill Adaptation for Reinforcement Learning in Dynamic Environments

arXiv:2609.11433v1 Announce Type: new Abstract: Skill adaptation frameworks based on reinforcement learning often require restrictive assumptions to maintain stability, such as fixed observations or t

safetyarxiv-cs-ro

Same Day, Same Story; One Day Ahead, a Different Signal: The Dual Validity of Financial Sentiment

arXiv:2609.11144v1 Announce Type: cross Abstract: Financial NLP has a standard workflow: validate a sentiment tool against human labels, then trust it to extract market signal. This assumes the two ev

Scores Alone Do Not Prove Discovery: The Discovery Certification Protocol for Auditing AI Research Agents

arXiv:2609.09219v1 Announce Type: cross Abstract: AI research agents combine prior knowledge, public sources, and experimental feedback to produce useful results. The Discovery Certification Protocol

SenseNova-U1.5: Towards Native Unified Visual Intelligence

arXiv:2609.11929v1 Announce Type: new Abstract: We launch SenseNova-U1.5, an 8B-MoT native unified multimodal model that understands, reasons about, and generates visual content within an encoder-free

safetyarxiv-cs-cv

Seven Sources of Physical AI Capability Formation

arXiv:2609.09627v1 Announce Type: new Abstract: Capabilities relevant to Physical AI can arise from materially different formation histories, yet existing taxonomies organized by morphology, architect

researcharxiv-cs-ai

SGA: Plug&Play Geometric Verification for Educational Video Synthesis

arXiv:2607.18116v2 Announce Type: replace-cross Abstract: Recent work leverages Large Language Models (LLMs) to generate executable code for pedagogical animations using libraries such as Manim. Howev

Single Microphone Own Voice Detection based on Simulated Transfer Functions for Hearing Aids

arXiv:2603.02724v2 Announce Type: replace-cross Abstract: This paper presents a simulation-based approach to own voice detection (OVD) in hearing aids using a single microphone. While OVD can signific

applicationsarxiv-cs-lg

Spectral Adapters for Segment Anything Model-based Segmentation of Colorectal Liver Metastases in Computed Tomography

arXiv:2609.11703v1 Announce Type: new Abstract: Accurate segmentation of colorectal liver metastases (CRLM) in contrast-enhanced computed tomography (CT) is important for response assessment, surgical

Structural priors for data-efficient language learning

arXiv:2609.11505v1 Announce Type: new Abstract: Efficient language learning requires methods to reduce the reliance on large data and computational resources. We investigate structural transfer: First

TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription

arXiv:2609.11904v1 Announce Type: new Abstract: Automatic Music Transcription (AMT) for guitar remains limited by three challenges: existing systems often fail to capture expressive techniques such as

applicationsarxiv-cs-lg

The Eloquence submission for Task 2 of the Interspeech 2026 MLC-SLM challenge

arXiv:2609.11724v1 Announce Type: new Abstract: This paper details the Eloquence team's approach to Task 2 of the 2nd MLC-SLM challenge at Interspeech 2026, which involves multilingual Multiple-Choice

safetyarxiv-cs-cl

The Illusion of Balanced Multimodal Sentiment Analysis: Beyond the Limits of Optimization-Based Methods

arXiv:2609.11247v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) remains constrained by modality imbalance, yet the field continues to rely on optimization-based balancing methods t

researcharxiv-cs-cl

The Truth Was Never Gone: Perfect Aliasing in Compliant-Context Truth Probes

arXiv:2609.10739v1 Announce Type: cross Abstract: A truth probe fitted where truthful reporting and a task's prescribed action coincide cannot distinguish those targets from its fitting labels alone.

Think Before You Link: Rarity, Reasoning, and Retrieval in Multilingual Entity Linking

arXiv:2609.10745v1 Announce Type: new Abstract: Multimodal entity linking grounds entity mentions in text and images to knowledge-base entries. These systems degrade on rare entities, but prior work m

Using Semantic Uncertainty to Estimate Transition Relevance in Turn-taking

arXiv:2609.10934v1 Announce Type: new Abstract: Turn-taking is a fundamental mechanism that governs when interlocutors speak and listen. Although Spoken Dialogue Systems (SDS) exploit a range of lingu

researcharxiv-cs-cl

Voice or Stereotype? Disentangling Acoustic and Content-Based Gender in Speech-to-Speech Models

arXiv:2609.09263v1 Announce Type: cross Abstract: Speech-to-speech (S2S) models now run inside dubbing, translation, and voice agents. Unlike text models, they hear the speaker's voice, which carries

When More Is Not Better: Component Anti-Synergy in a P300 Speller

arXiv:2609.10961v1 Announce Type: new Abstract: P300 brain-computer interface (BCI) spellers can provide hands-free communication for people with severe motor impairments. Modern pipelines combine mul

safetyarxiv-cs-lg

When Noise Fabricates Bias: The Fragility of LLM-as-a-Judge Bias Measurement under Noisy Text

arXiv:2609.11067v1 Announce Type: new Abstract: Large language models are increasingly used as judges to measure social bias in text, yet the passages they judge are often noisy, containing typos, inf

safetyarxiv-cs-cl

When Synthetic Data Hurts: On Catastrophic Forgetting in Skill Retrieval for LLM Agents

model-releasesarxiv-cs-lg

arXiv:2609.10750v1 Announce Type: cross Abstract: LLM agents increasingly rely on external skills retrieved at runtime, making skill selection from large repositories a critical challenge. We present

Local Ai

(Whose defaults?) Is artificial intelligence reorienting archaeological methods?

arXiv:2609.11198v1 Announce Type: cross Abstract: Generative AI and the practice of 'vibe coding' are changing how archaeologists carry out computational research, but their effects on the discipline'

local-aiarxiv-cs-cl

Why Sample What You Can Enumerate? Exact Policy Optimization for Genomic Tool Selection

arXiv:2609.10221v2 Announce Type: new Abstract: Reinforcement learning over a frozen reasoner has become a common recipe for teaching a policy which external tools to invoke. We show that this recipe

Tutorials

World in World: Explore the World with World Models

arXiv:2609.11548v1 Announce Type: new Abstract: Autoregressive video world models enable interactive, long-horizon exploration, but flexible control remains challenging. Exploring a source video from

tutorialsarxiv-cs-cv

Agents

A Computational Implementation of a Goal-Directed Theory of Affect

arXiv:2609.06654v1 Announce Type: new Abstract: Computational modeling of emotion has long faced a tension between descriptive, 'snapshot-based' appraisal models and granular, signal-driven architectu

agentsarxiv-cs-ai

A Decade of Bayesian Optimization for Controller Tuning and Robot Learning: Tutorial, Review, and Future Prospects

model-releasesarxiv-cs-ro

arXiv:2609.09403v1 Announce Type: new Abstract: In the past decade, Bayesian optimization (BO) has emerged as a powerful and adaptable framework for automatic controller tuning and robot learning. Thi

A Dominant Diffuse Phase in the Sparse Autoencoder Phase Diagram

arXiv:2609.10299v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are increasingly used to recover interpretable features from neural-network activations, yet systematic feature co-occurrence

researcharxiv-cs-lg

A Layered Analysis of Disagreement And Answer Quality in Multi-Agent LLM Debate

arXiv:2609.08016v1 Announce Type: new Abstract: Multi-agent debate, in which several LLMs exchange arguments before answering, is widely assumed to improve answer quality by surfacing genuine disagree

Tutorials

A Statistical Approach to Estimating Sample Size of Machine Learning Models

arXiv:2609.09547v1 Announce Type: new Abstract: Sample size determination for machine learning (ML) prediction models is challenging because conventional power analysis typically requires the predicto

tutorialsarxiv-cs-lg

A Tool-Augmented, GPT-4 Chatbot for Real-Time Repository Data Analysis

arXiv:2609.07586v1 Announce Type: new Abstract: Software repositories contain vast amounts of data on code contributions, bug reports, and project activities, yet this information remains challenging

A TTP by TTP Approach: Precise Malware Detection via Malicious TTP Recognition

arXiv:2609.06579v1 Announce Type: cross Abstract: Machine learning methods, and especially neural networks, are now routinely used for malware detection in network traffic. Though very effective, syst

researcharxiv-cs-ai

A visual large language foundational model for medical image recognition using clinician-oriented social media

arXiv:2609.06914v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities across diverse domains, showing considerable potential in medicine. However, their ap

AAS-RAIL: Improving Information Extraction for Asset Administration Shells through Retrieval-Augmented In-Context Learning

arXiv:2609.07334v1 Announce Type: new Abstract: The Asset Administration Shell (AAS) is a cornerstone of Industry 4.0 and the Digital Product Passport, providing standardized digital representations o

researcharxiv-cs-ai

AdaCultureSafe: Adaptive Cultural Safety Grounded by Cultural Knowledge in Large Language Models

arXiv:2603.08275v2 Announce Type: replace-cross Abstract: With the global proliferation of Large Language Models (LLMs), cultural safety, defined as the ability to generate respectful and appropriate

Adaptive Shared Control with Online Bounded-Rational Human Behavior Estimation

model-releasesarxiv-cs-ro

arXiv:2609.10215v1 Announce Type: new Abstract: This work considers adaptive shared human-robot control for nonlinear control-affine systems, where the assumption of a fully rational human is relaxed

AgroVisNet: A lightweight Convolutional Network and the BD-PlantDX Expert-Validated Benchmark for Radish, Potato and Pointed Gourd Disease Classification

arXiv:2609.10469v1 Announce Type: new Abstract: Automated plant disease diagnosis is increasingly deployed on farmer-held devices in regions where agronomic expertise is scarce and network connectivit

Local Ai

ALIGN-HOLD: Experience Alignment for Real-Time Hold Control in Large-Scale Ride-Hailing Matching at DiDi

arXiv:2609.09685v1 Announce Type: new Abstract: Real-time hold control is a high-leverage mechanism in large-scale ride-hailing systems: by selectively deferring driver-order pairs, the platform can w

local-aiarxiv-cs-lg

AlignDiff: Exploiting Model-Intrinsic Information for Better Preference Data Selection

arXiv:2609.05899v1 Announce Type: cross Abstract: Aligning large language models with human preferences remains a challenge, primarily due to the critical role of preference data quality in effective

Agents

An Efficient and Effective Agentic Group Shilling Attack on Recommender Systems

arXiv:2609.09551v1 Announce Type: cross Abstract: Recommender systems have become core infrastructure for modern online platforms, personalizing content at scale and strongly influencing what users se

agentsarxiv-cs-cl

An Explainable Machine Learning Framework for Predicting Blood-Brain Barrier Permeability Using Molecular Descriptors

arXiv:2609.10012v1 Announce Type: new Abstract: Blood-brain barrier (BBB) permeability is a critical determinant in the development of central nervous system therapeutics because it directly influence

researcharxiv-cs-lg

Arti-JEPA: Adapting Video World Model to Real-Time MRI of the Vocal Tract for Speech-Production Analysis

arXiv:2609.09757v1 Announce Type: cross Abstract: Real-time MRI (rtMRI) captures the dynamics of the entire vocal tract during speech, but labeled data are scarce and the modality - single-slice, gray

applicationsarxiv-cs-cv

Artificial Intelligence Literacy and Sustainable Development: An Ethical Governance and Development Goals Framework

arXiv:2609.10489v1 Announce Type: new Abstract: AI literacy provides foundational competencies that support ethical, transparent, and sustainable technological development, although higher-order capab

applicationsarxiv-cs-cv

ASDA: Automated Skill Distillation and Adaptation for Financial Reasoning

arXiv:2603.16112v2 Announce Type: replace-cross Abstract: Adapting large language models (LLMs) to specialized financial reasoning typically requires expensive fine-tuning that produces model-locked e

Bayesian deep learning integration of geophysical and drilling data for 3D prediction of copper mineralization and drill targeting: a case study from the Kogodai prospect, Rudny Altai

arXiv:2609.09246v1 Announce Type: cross Abstract: Exploration drill targeting in structurally complex terranes is hindered by sparse sampling, heterogeneous datasets, and the ambiguity of geophysical

applicationsarxiv-cs-lg

Belief-State Engine: Augmenting LLMs for Principled Planning Under Partial Observability

arXiv:2609.10036v1 Announce Type: cross Abstract: Large language model agents produce fluent action sequences across a wide range of tasks, yet they fail in characteristic ways once the environment be

safetyarxiv-cs-lg