Search: “evaluation”

Continual Field-Adaptive Models (CFAMs) for Post-Deployment Physical AI

arXiv:2609.04552v1 Announce Type: cross Abstract: Unattended interactive autonomy - machines that step into danger in place of humans and complete tasks with human tools - remains a missing capability

local-aiarxiv-cs-ai

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Model Releases

Continual Graph Memory for Adaptive Recommendation under Intent Drift

DGX agent

arXiv:2609.04651v1 Announce Type: new Abstract: This paper studies adaptive recommendation under intent drift, where feedback from each recommendation outcome can reveal whether the relational evidenc

model-releasesarxiv-cs-ai

7 Sept 2026

CrossDepth: Geometry-Constrained Attention for Generalizable Multi-View Surround Depth Estimation

arXiv:2609.05397v1 Announce Type: new Abstract: Reliable 3D understanding of the surrounding environment is a core requirement for autonomous driving. Multi-view surround camera rigs provide broad sce

agentsarxiv-cs-cv

Dynamic Adaptation of the LLM Context for Generating Routines with Coupled Semantics

arXiv:2609.04570v1 Announce Type: cross Abstract: LLM-based code generation fails when correctness depends on execution-dependent coupling: the meaning of one routine is defined by the runtime behavio

agentsarxiv-cs-ai

ElderBench: Benchmarking Autonomous Mobile Agents for Older Adults

arXiv:2609.04850v1 Announce Type: new Abstract: While autonomous mobile agents hold great potential for assisting older adults with smartphone usage, existing GUI benchmarks mainly rely on explicit, g

First Things First: Teaching LLM-Based Agents to Prioritize Must-Haves before Nice-to-Haves

arXiv:2609.05224v1 Announce Type: new Abstract: Recent progress in multimodal large language models (MLLMs) has fueled significant enthusiasm in their potential to act as autonomous agents for real-wo

agentsarxiv-cs-cv

From Interaction Traces to Persistent Skills: Online Evolution for Computer-Use Agents

arXiv:2609.04869v1 Announce Type: new Abstract: Computer-use agents can execute increasingly complex tasks in graphical interfaces, but their interaction experience is typically transient: procedural

From Plausible to Actionable: A Position on LLM Self-Explanations

arXiv:2607.15957v2 Announce Type: replace Abstract: Large Language Models (LLMs) can generate natural language explanations that rationalize their own decisions, a phenomenon commonly referred to as s

researcharxiv-cs-cl

How a Chatbot's Response Style Shapes a Classroom: A Multi-Agent Simulation of Students Consulting AI

arXiv:2609.05018v1 Announce Type: cross Abstract: LLM-based chatbots are increasingly used as everyday confidants. Because they are designed to maximize user satisfaction, they can respond with excess

How Faithful Is Attribution for Sales Forecasting? A Counterfactual Study

arXiv:2609.04797v1 Announce Type: new Abstract: Deep models for sales forecasting, such as WaveNet-style dilated convolutional networks, are accurate but opaque: when a single model predicts sales for

researcharxiv-cs-lg

Iris: Climbing to the Search Frontier

arXiv:2609.04304v1 Announce Type: new Abstract: We present Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the data pipeline and training recipe be

KVMem: Virtualizing Million-Token Agent Workspaces on a Consumer GPU

arXiv:2609.04852v1 Announce Type: new Abstract: Modern LLM agents operate in persistent workspaces whose accumulated history can exceed both GPU KV capacity and the model's native context window. Exis

Learning from VAE Errors to support ECG-based Differential Diagnosis of Myocardial Scar

arXiv:2609.05294v1 Announce Type: new Abstract: Late Gadolinium Enhancement (LGE) on cardiac magnetic resonance is a key marker of myocardial scar, but its limited accessibility motivates routine ECG-

local-aiarxiv-cs-lg

Hardware

Low-Latency Spell Correction for Japanese Music Search Queries

arXiv:2609.04262v1 Announce Type: cross Abstract: Spell correction for Japanese search queries presents unique challenges due to the co-existence of four writing scripts (Latin/romaji, hiragana, katak

hardwarearxiv-cs-lg

Applications

LUMIN: Lightweight Universal Manufacturing Inspection Network for Anomaly Detection

arXiv:2609.04775v1 Announce Type: new Abstract: Industrial anomaly detection faces two engineering bottlenecks: memory bank construction latency and inference efficiency. Traditional sampling algorith

applicationsarxiv-cs-cv

MABPD: Multi-Agent Bias Probing & Detection via Structured Argument Debate

arXiv:2609.04841v1 Announce Type: cross Abstract: Media bias in news articles operates through subtle linguistic cues---loaded language, selective framing, and strategic omission---that resist single-

Moral Competence Before Moral Content: Why LLM Agents Lack the Prerequisites for Coherent Alignment

arXiv:2609.05036v1 Announce Type: new Abstract: AI alignment requires AI systems to adhere to human norms, values, or intentions. Under value pluralism there is no correct target, but a shared prerequ

safetyarxiv-cs-ai

Motion-Omni: End-to-End Joint Speech and Full-Body Motion for Spoken Dialogue

arXiv:2609.04250v1 Announce Type: cross Abstract: An avatar that holds a conversation should decide what to say and to move while saying it, yet these abilities live in separate model families: spoken

safetyarxiv-cs-cv

MultihopSpatial: Multi-hop Compositional Spatial Reasoning Benchmark for Vision-Language Model

arXiv:2603.18892v2 Announce Type: replace-cross Abstract: Spatial reasoning is foundational for Vision-Language Models (VLMs), particularly when deployed as Vision-Language-Action (VLA) agents in phys

NOTAI.AI: Explainable Detection of Machine-Generated Text via Curvature and Feature Attribution

arXiv:2603.05617v2 Announce Type: replace Abstract: We present NotAI.AI, an explainable AI-generated text detection system. Instead of returning only a binary label or confidence score, the system sho

local-aiarxiv-cs-cl

One Word, Different Action: A Real-Robot Benchmark for Language-Conditioned Embodied Reasoning

model-releasesarxiv-cs-ro

arXiv:2609.05260v1 Announce Type: new Abstract: Natural-language instruction changes can directly alter robot behavior. A reliable embodied system should preserve its action when the task is unchanged

PerfReasoning: How Well Do LLMs Reason on Hardware Performance?

arXiv:2609.04476v1 Announce Type: new Abstract: Performance modeling is central to hardware design and software optimization, yet constructing these models requires structured reasoning about computat

PRICE: A Systematic Study of LLM Adaptation Choices for Bitcoin Price Forecasting

arXiv:2609.05235v1 Announce Type: cross Abstract: Cryptocurrency markets exhibit extreme volatility and non-stationary dynamics that challenge conventional forecasting methods. Although Large Language

Rethinking Indirect Prompt Injection as a Test-Time Search Problem

arXiv:2609.04495v1 Announce Type: new Abstract: We formulate indirect prompt injection as a test-time search over a task-dependent attack surface induced by the environment, user task, and injection t

agentsarxiv-cs-ai

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

arXiv:2609.05324v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchma

Safety for Whom? Boundary-Aware Self-Distillation for Controlled LLM Safety Refusal

arXiv:2609.04482v1 Announce Type: new Abstract: Safety alignment is usually posed as a topic-level question: is this subject harmful? Deployments ask a narrower one. A civics tutor and a public-sector

safetyarxiv-cs-cl

SoK: AI-Augmented Binary Reversing

arXiv:2606.17398v2 Announce Type: replace-cross Abstract: Binary reversing is fundamental to software understanding, vulnerability discovery, malware investigation, and firmware auditing. However, it

agentsarxiv-cs-ai

Think-Verify-Revise: Neuro-Symbolic Visual Reasoning with Vision-Language Models and Dynamic Logic Tensor Networks

model-releasesarxiv-cs-cv

arXiv:2609.05388v1 Announce Type: new Abstract: Visual reasoning tasks require a system to jointly perceive visual content and apply formal relational constraints---a combination that neither pure neu

TROVE: Adaptive Agent Skill Orchestration via Trace-Grounded Route Validation and Editing

arXiv:2609.05019v1 Announce Type: new Abstract: Agents tend to optimize, select, or constrain execution structures before decisive runtime outcomes are observed. However, such pre-execution commitment

local-aiarxiv-cs-ai

VERGE: Verification-Enhanced Refinement for Grounded Extraction of Early-Onset Colorectal Cancer Symptoms in Clinical Notes

arXiv:2609.04366v1 Announce Type: new Abstract: Early-onset colorectal cancer is increasing among younger adults, yet red-flag symptoms in this age group have no evidence-based guidelines for follow-u

agentsarxiv-cs-cl

VoxelFix: Post-Hoc Semantic Correction of Completed 3D Voxel Maps

arXiv:2609.05114v1 Announce Type: new Abstract: Semantic 3D maps are increasingly constructed automatically for aerial robotics by integrating learned semantic predictions into 3D representations. Whi

local-aiarxiv-cs-cv

What Does Multi-Harness RL Learn? Credit Assignment and Portability in Coding Agents

arXiv:2609.04518v1 Announce Type: new Abstract: Agent reinforcement learning (RL) increasingly runs through full execution harnesses, and a multi-harness recipe mixes two choices: exposing the policy

A Large Open Multi-Energy Corpus of Soil Compaction Tests, with Machine-Learning Baselines

arXiv:2609.03337v1 Announce Type: new Abstract: Every engineered fill is specified by a maximum dry density and an optimum moisture content. Each determination needs a full Proctor test. Published cor

A Quantitative Comparison of Centralised and Distributed Reinforcement Learning-Based Control for Soft Robotic Arms

arXiv:2511.02192v3 Announce Type: replace Abstract: This paper presents a quantitative comparison between centralised and distributed multi-agent reinforcement learning (MARL) architectures for contro

safetyarxiv-cs-ro

ARCOS: Zero-shot Boundary Localization for Corneal Layer Segmentation Across Optical Coherence Tomography Devices

arXiv:2609.03668v1 Announce Type: new Abstract: Accurate segmentation of corneal layers in optical coherence tomography (OCT) is essential for quantitative assessment of corneal morphology, including

researcharxiv-cs-cv

BASP: Communication-Efficient Batch-Aware Sequence Parallelism for LLM Training

arXiv:2609.03151v1 Announce Type: cross Abstract: Long-context reasoning for large language models (LLMs) is becoming increasingly important, but training over long sequences remains challenging due t

Beyond Accuracy: Community Perspectives on Machine Translation

model-releasesarxiv-cs-cl

arXiv:2606.09655v2 Announce Type: replace Abstract: Despite remarkable progress in machine translation (MT), non-AI communities have raised growing concerns about MT systems, suggesting a noticeable g

Applications

Beyond Small Patches: Black-Box Detection and Purification of Diverse Backdoor Triggers

arXiv:2609.03139v1 Announce Type: new Abstract: Deep neural networks (DNNs) are increasingly deployed in real-world vision systems, yet their predictions can be covertly manipulated by backdoor attack

applicationsarxiv-cs-cv

Can LLMs Extract Architectural Design Decisions from Source Code Commits? - A Preliminary Exploratory Study

arXiv:2609.03721v1 Announce Type: cross Abstract: Context: Architectural Design Decisions (ADDs) capture the rationale behind the structure and evolution of software systems but are rarely documented

Cooperative Multi-Task Semantic Communication for Joint Classification and Regression Tasks

arXiv:2609.03977v1 Announce Type: cross Abstract: Multi-Task semantic communication (SemCom) prioritizes simultaneous execution of multiple tasks over bit-accurate reconstruction in future intelligent

CORE: Improving Compositional Reasoning in MLLM Embedding via Reranker Distillation

arXiv:2609.04083v1 Announce Type: cross Abstract: MLLM-based embedding models remain limited in compositional retrieval, often failing to distinguish scenes containing the same concepts but different

Detecting Conversational Mental Manipulation with Intent-Aware Prompting

arXiv:2412.08414v2 Announce Type: replace Abstract: Mental manipulation severely undermines mental wellness by covertly and negatively distorting decision-making. While there is an increasing interest

researcharxiv-cs-cl

Efficient Semantic Understanding from Digital Foveation

arXiv:2609.04088v1 Announce Type: new Abstract: Dense semantic segmentation allocates computational resources uniformly across the entire image, regardless of scene complexity or task relevance. Inspi

researcharxiv-cs-cv

EraseSAE: Surgical Concept Erasure in Text-to-Video Diffusion Models via Sparse Autoencoders

arXiv:2609.03629v1 Announce Type: cross Abstract: Recent advances in text-to-video (T2V) diffusion models have demonstrated remarkable generative capabilities, yet their reliance on loosely curated tr

safetyarxiv-cs-ai

Tutorials

From Nowcasting to Forecasting: Adapting a Reanalysis-Trained

arXiv:2609.03763v1 Announce Type: new Abstract: Accurate cloud-cover forecasts are important for temperature prediction, radiation forecasting, and solar-power operations. Short-range forecasting meth

tutorialsarxiv-cs-lg

From Zero to Hero: An Open LLM Ecosystem for Armenian

model-releasesarxiv-cs-cl

arXiv:2609.03350v1 Announce Type: cross Abstract: Pretraining data for Armenian, a morphologically rich and low-resource language, is scarce, and no open Armenian LLM has been released with the data a

How Far Can Synthetic Data Take Thai OCR?

arXiv:2609.03595v1 Announce Type: cross Abstract: We investigate what makes synthetic OCR supervision transfer to real Thai documents and use the resulting insights to build Wayu-Paxa-OCR-Zero, a Thai

IchthyoNoma: Nomenclature and Context Sensitivity of Zero-Shot Biological Vision--Language Models for Bangladeshi Freshwater Fish Recognition

arXiv:2609.03985v1 Announce Type: cross Abstract: Zero-shot vision-language models (VLMs) are increasingly used as training-free species recognizers, but reported accuracy can reflect more than visual

safetyarxiv-cs-cl