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Paris-based Arlequin AI SAS today announced it raised €28 million, about $32 million, in new funding to accelerate development of a new AI model architecture based on a different type of network that

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Agents

Artificial Intelligence-Assisted Digital Inventory of Cultural Heritage & Traditional Knowledge: Case for Indonesian Open Digital Library of Culture

DGX agent

arXiv:2609.08105v1 Announce Type: new Abstract: The Indonesian Digital Library of Culture (Perpustakaan Digital Budaya Indonesia, PDBI; budaya-indonesia.org) is a participatory platform that has colle

agentsarxiv-cs-ai

10 Sept 2026

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

AttnCompress: Dynamic Attention-Guided Trajectory Compression for Software Engineering Agents

arXiv:2609.08318v1 Announce Type: cross Abstract: The transition from human-centric assistance to Autonomous Software Engineering (ASE) agents has enabled the resolution of complex real-world SE tasks

Attribution in Scientific Literature: New Benchmark and Methods

arXiv:2405.02228v4 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly generate citation-backed responses, yet citation hallucination remains a major challenge for trustwo

Audio-Maestro: Enhancing Large Audio-Language Models with Tool-Augmented Reasoning

arXiv:2510.11454v2 Announce Type: replace-cross Abstract: Recent advancements in large multimodal models (LMMs) have shown strong capabilities in audio understanding. However, most systems rely solely

BETA-Labeling for Multilingual Dataset Construction in Low-Resource IR

arXiv:2602.14488v3 Announce Type: replace-cross Abstract: IR in low-resource languages remains limited by the scarcity of high-quality, task-specific annotated datasets. Manual annotation is expensive

safetyarxiv-cs-ai

Beyond 'AI Helps Humans': Decision-Targeted Evaluation Design for Human-Agent Teams in the Agentic Era

arXiv:2609.05527v1 Announce Type: new Abstract: Wherever a coding agent works under engineer supervision, or a clinical model assists a radiologist, the deployment question is whether to keep the huma

Beyond Similarity: Foundation Models as an Efficient Backbone for Training-Free Composed Video Retrieval

arXiv:2609.10008v1 Announce Type: new Abstract: Composed video retrieval (CoVR) searches a gallery for the target video that realizes a natural-language modification of a source clip. However, at gall

Can Artificial Intelligence Support Healthcare and Mental Health Through Early Cyberbullying Detection ? The Impact of Emotion-Aware AI on Proactive Online Safety

arXiv:2609.09735v1 Announce Type: cross Abstract: Healthcare systems, mental health, and public well-being are increasingly affected by cyberbullying and harmful online interactions. This paper presen

Closing the Consistency Gap: Self-Evolving Agents That Learn to Stay on Course

arXiv:2609.08832v1 Announce Type: new Abstract: Large language model (LLM)-powered agents can be accurate on average yet unreliable in production, a discrepancy that has been observed but remains larg

Agents

Compiling VGDL into Causal Models

arXiv:2609.05459v1 Announce Type: new Abstract: Reinforcement learning and large language models often struggle to accurately capture the causal mechanics of game environments. Standard reinforcement

agentsarxiv-cs-ai

Cross-Model Agreement as a Deployment-Time Reliability Signal for Automatic Polyp Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.10495v1 Announce Type: new Abstract: In real-time colonoscopy, ground-truth annotations are unavailable at inference, so polyp segmentation models can fail silently. We propose Referee-Base

Decoupled Self-Forcing Distillation for Streaming Talking Head Generation

arXiv:2609.10317v1 Announce Type: new Abstract: Streaming talking-head generation produces each frame as its driving audio arrives, yet fidelity and efficiency have so far pulled in opposite direction

safetyarxiv-cs-cv

Local Ai

Detokenization Leaks: Reconstructing Local LLM Outputs From Cache Traces

arXiv:2609.06674v1 Announce Type: cross Abstract: We present a new attack that reconstructs the text generated by locally hosted LLMs by observing CPU cache activity during detokenization. Unlike prio

local-aiarxiv-cs-ai

Do Web Agents Investigate Before They Decide?

arXiv:2602.05354v3 Announce Type: replace Abstract: Autonomous web agents are increasingly deployed in moderation and policy enforcement, where correct decisions often depend on evidence that is not i

Dynamics of meaning: Towards the Evaluation of Diachronic Semantic Change in Sinhala

arXiv:2609.08609v2 Announce Type: replace Abstract: Tracking semantic change in low-resource languages across extensive historical timelines presents significant challenges due to data scarcity and th

Applications

Efficient Diversity-based Experience Replay for Deep Reinforcement Learning

arXiv:2410.20487v5 Announce Type: replace Abstract: Experience replay is widely used to improve learning efficiency in reinforcement learning by leveraging past experiences. However, existing experien

applicationsarxiv-cs-lg

Evaluating and Improving Evidence-Grounded Fact-Checking in LLMs via Multi-Round Evidence Ablation

arXiv:2609.08943v1 Announce Type: cross Abstract: Automatic fact-checking systems assess the veracity of claims given evidence from relevant documents. Large Language Models (LLMs) have demonstrated s

Every Activation Boosted: Scaling General Reasoner to 1 Trillion Open Language Foundation

arXiv:2510.22115v2 Announce Type: cross Abstract: We introduce Ling 2.0, a series reasoning-oriented language foundation built upon the principle that every activation boosts reasoning capability. Des

FATS: A Prompt Injection Attack Utilizing Feign Security Agents with Deceptive Few-shots Learning

arXiv:2410.08776v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) face significant security risks despite their advanced capabilities. While techniques like Reinforcement Learning

From Fixed Keys to Readable Schemas: Small Language Models for Vehicle Agent Function Calls

arXiv:2609.09476v1 Announce Type: cross Abstract: In-vehicle assistants must translate natural-language requests into accurate vehicle function calls under strict memory and latency constraints, makin

From Scores to Evidence: Auditable Decisions Can Improve Speech Deepfake Detection

arXiv:2609.08899v2 Announce Type: replace-cross Abstract: Speech deepfakes can mimic a speaker's voice convincingly enough to deceive listeners and automated systems. This has driven strong progress i

researcharxiv-cs-cl

From the Fluency Fallacy to the Micro-to-Macro Validity Gap: Opportunities and Pitfalls of LLMs in Social Simulation

arXiv:2507.19364v3 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) into social simulation has generated considerable enthusiasm, but also raises substantial methodolog

safetyarxiv-cs-ai

Hierarchical and Permutation-Invariant Feature Transformation Learning via Policy-Guided Embedding Search

arXiv:2609.10225v1 Announce Type: new Abstract: Feature transformation improves predictive performance on tabular data by constructing informative abstractions from raw features. Recent generative app

safetyarxiv-cs-lg

How AI Models Manage Epistemic Authority: A Taxonomy and Comparative Analysis of Responses to User Disagreement

arXiv:2609.07662v1 Announce Type: cross Abstract: Large language models are increasingly used as sources of advice and information, including in high-stakes settings, yet little is known about how the

Applications

IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier

arXiv:2609.10494v1 Announce Type: new Abstract: Enterprises deploy systems, not checkpoints. Usable capability depends jointly on weights, serving route, precision, output contract, and harness, yet a

applicationsarxiv-cs-cl

IMU-Centric Moving Horizon Estimation for Lateral Dynamics Estimation Across Vehicles and Grip Conditions

model-releasesarxiv-cs-ro

arXiv:2609.10202v1 Announce Type: cross Abstract: Accurate estimation of lateral vehicle dynamics near the adhesion limit is important for stability control and high-performance driving, but lateral v

Kernel-Complexity Edge Sanitization for Training-Free Defense against Structural Graph Attacks

arXiv:2609.09698v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications, yet they remain highly vulnerable to adversarial attacks that

Knowing Your Uncertainty -- On the application of LLM in social sciences

arXiv:2512.05461v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly being integrated into computational social science research, yet their blackboxed training and design

Learning to Fly: Stable Vision-Guided UAV Servoing with Compact Target-Centric Cues and Reinforcement Learning

arXiv:2609.09234v1 Announce Type: cross Abstract: Vision-guided reinforcement learning for Unmanned Aerial Vehicles (UAVs) remains challenging due to unstable policy optimisation, aggressive explorati

safetyarxiv-cs-lg

LeCor: Learning to Be Corrected by Meta-Learned Test-Time Training for Interactive 3D Lung-Tumour Segmentation

arXiv:2609.09477v1 Announce Type: new Abstract: Delineating lung tumours on computed tomography (CT) takes a considerable share of the time spent on radiotherapy planning, and a contour proposed by a

Local Ai

LSP-DETR: Efficient and Scalable Nuclei Segmentation in Whole-Slide Images

arXiv:2601.03163v2 Announce Type: replace Abstract: Background and Objective: Precise and scalable instance segmentation of cell nuclei is a fundamental prerequisite for computational pathology, yet g

local-aiarxiv-cs-cv

Monte Carlo-Based Ex-Ante Assessment of the Green Benefits of an AI-Driven Smart Agriculture Platform in Hainan

arXiv:2609.06737v1 Announce Type: new Abstract: Smart agriculture platforms are widely regarded as key carriers for implementing China's pesticide and fertilizer reduction, water-saving and carbon-red

Morphological Decoupling-Based Skeletal Classification for Clinical Assessment of Malocclusion

arXiv:2609.09801v1 Announce Type: cross Abstract: Malocclusion skeletal grading is a fundamental task in orthodontics, critical for diagnosis and treatment planning. Traditionally, cone-beam computed

MOSAIC: A Universal Agent-Level Interface for Cross-Paradigm Agent Mixing and Human-AI Collaboration

model-releasesarxiv-cs-lg

arXiv:2603.01260v2 Announce Type: replace Abstract: Existing infrastructure cannot deploy agents from different decision-making paradigms within the same environment, making fair cross-paradigm compar

Multi-Functional Embedding Models for Funder Name Disambiguation in Scientific Publication Records

arXiv:2609.09984v1 Announce Type: new Abstract: Understanding the historical allocation and distribution of research funding advances our knowledge of how scientific research is supported across field

Multi-Pass, Multi-View Blended Learning for High-Fidelity Volumetric CT Synthesis from Chest X-Rays

arXiv:2609.09920v1 Announce Type: new Abstract: Reconstructing volumetric Computed Tomography (CT) from a single 2D chest radiograph (CXR) is an ill-posed inverse problem, further complicated by the s

Noise Adaptive Streaming Audio-Visual Speech Token Enhancement for Robust Full-Duplex Spoken Dialogue Models

arXiv:2609.08390v1 Announce Type: cross Abstract: Full-duplex spoken dialogue systems enable simultaneous listening and speaking, but their audio-only perception often fails under background noise and

ObGynLongBench: Revealing the Evidence-to-EHR Gap in Longitudinal EHR Decision-Making

arXiv:2609.07601v1 Announce Type: cross Abstract: The application of large language models (LLMs) to personalized medical assistants has garnered growing interest. However, existing medical benchmarks

On-Policy Distillation for Vision-Language Model Adaptation, an Effective Paradigm on Low-Quality Multimodal Data

arXiv:2609.10321v1 Announce Type: new Abstract: Knowledge distillation offers an efficient route to transfer a task-adapted vision-language teacher to a compact student. The training target in current

safetyarxiv-cs-cl

One Loop, Two Gains: Can Active Learning win the Lottery for Free?

arXiv:2609.10311v1 Announce Type: cross Abstract: The lottery ticket hypothesis posits the existence of winning tickets: sparse subnetworks that, when trained in isolation from their original initiali

OntologyAligner: Ontology-Aligned Retrieval and Hierarchy-Guided Large Language Model Reranking for Biomedical Ontology Normalization

arXiv:2609.10055v1 Announce Type: cross Abstract: Biomedical ontology normalization maps free-text expressions to standardized concepts, enabling consistent integration and analysis of biomedical data

Open Tabular Insight Extraction: Where Do We Stand, and Where Should We Go?

arXiv:2609.07629v1 Announce Type: cross Abstract: Democratizing access to the knowledge held in large corpora of tables such as data lakes is emerging as a central research challenge. Research in this

Optimal Low-Rank Quantum State Tomography with Bounded-Sample Joint Measurements

arXiv:2609.10514v1 Announce Type: cross Abstract: We determine the optimal sample complexity of low-rank quantum state tomography when each measurement may act jointly on at most t samples. For suffic

Performance of Clinical AI System and Physicians and Frontier Language Models in primary care diagnostics

arXiv:2609.09070v1 Announce Type: cross Abstract: Clinical AI evaluation should encompass diagnosis and management after adaptive information gathering. We compared Doctorina, eight physicians and fou

PhysMAS: Physics-Grounded Multi-Agent Synthesis of Compositional 4D Gaussians

arXiv:2609.07174v1 Announce Type: new Abstract: Efficient, fully automatic, and physically plausible 4D Gaussian synthesis is an important goal for dynamic scene generation. Recent physics-based metho

Applications

Quantile-Led Feature Extraction for Multi-Horizon Predictive Maintenance in Industrial Manufacturing Systems

arXiv:2609.07533v1 Announce Type: new Abstract: In data-driven predictive maintenance (PdM), feature extraction is usually treated as fixed preprocessing: a descriptor set is chosen once and reused wh

applicationsarxiv-cs-ai