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ExecCritic: Learn to Test, Test to Improve for Coding Agents

arXiv:2609.09133v1 Announce Type: new Abstract: Execution feedback can guide coding agents toward correct repository repairs, but only when the tests capture the behavior requested by the issue. Agent

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Experimental Analysis of Productive Interaction Strategy with ChatGPT: User Study on Function and Project-level Code Generation Tasks

DGX agent

arXiv:2508.04125v2 Announce Type: replace-cross Abstract: The application of Large Language Models (LLMs) is growing in the productive completion of Software Engineering tasks. Yet, studies investigat

model-releasesarxiv-cs-ai

10 Sept 2026

ExpertLens: Visualizing Embedding Spaces for Post-Hoc Explainability in MoE Enhanced Retrievers

arXiv:2609.06155v1 Announce Type: cross Abstract: Neural models, including dense retrievers, have been widely adopted in Information Retrieval (IR), often delivering state-of-the-art performance. Desp

Explainable Deep Learning for Price-Trade Dynamics: From Black-Box Forecasts to Effective Parametric Models

arXiv:2609.06085v1 Announce Type: cross Abstract: Understanding the joint dynamics of prices and trades is central to market microstructure, where returns and order flow interact through nonlinear and

Explainable Token-level Noise Filtering for LLM Fine-tuning Datasets

arXiv:2602.14536v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have seen remarkable advancements, achieving state-of-the-art results in diverse applications. Fine-tuning, an im

Agents

Explaining AI Agents Through Execution Traces

arXiv:2609.06063v1 Announce Type: new Abstract: AI Agents are increasingly deployed in real-world settings, where they interact with external tools and make sequential decisions with limited human ove

agentsarxiv-cs-ai

Explaining f-Divergence-Based Regularization via Local Curvature and Sharpness-Aware Minimization

model-releasesarxiv-cs-lg

arXiv:2609.09367v1 Announce Type: new Abstract: Divergence-based regularization and Sharpness-Aware Minimization (SAM) are two prominent approaches for improving generalization in deep learning, both

Exploring Bottom-Up Clustering for Creating Semantic IDs

arXiv:2609.08310v1 Announce Type: cross Abstract: The success of generative retrieval has largely been attributed to the use of Semantic IDs, which improve over arbitrary item-level identifiers such a

Exposing Weaknesses in Emotion Recognition in Conversations

arXiv:2609.05806v1 Announce Type: new Abstract: Emotion Recognition in Conversations (ERC) aims to identify speakers' emotions in multi-turn dialogue. Accurate emotion recognition can support a wide r

False positive bias in AI-powered speech-based cognitive screening for multilingual English speakers in the UK

arXiv:2602.13047v2 Announce Type: replace Abstract: Conversational speech reveals early signs of cognitive decline, including dementia and mild cognitive impairment (MCI). AI models show promise for s

safetyarxiv-cs-cl

Tutorials

Fast Constraint Extraction for Corrective Control under STL Specifications via Logical Dependency Tracking

arXiv:2609.09439v1 Announce Type: cross Abstract: Ensuring the satisfaction of Signal Temporal Logic (STL) specifications under uncertainty is challenging, as reachability-based monitoring provides gu

tutorialsarxiv-cs-ro

FastE: Readout-Triggered Token Compression for LLM Embedding Inference

arXiv:2609.08407v1 Announce Type: new Abstract: In this study, we identify depth-dependent prefix redundancy in final-readout LLM embedding models, notably across representative backbones including Qw

safetyarxiv-cs-ai

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

Federated Learning for Cross-Modality Medical Image Segmentation via Augmentation-Driven Generalization

arXiv:2602.20773v2 Announce Type: replace Abstract: Purpose: Developing generalizable medical image segmentation models is challenging because imaging data are distributed across institutions and diff

Feyospace-v1: How the Cyber Mercury Seven Trained Frontier Cyber Models

arXiv:2609.08418v1 Announce Type: new Abstract: Training capable cyber agents is often treated primarily as a problem of model scale, yet open-weight post-training is constrained more directly by the

Field Converter: Geometry-Initialized Temporal Residual Refinement for World-Grounded Player Pose Estimation from Soccer Broadcasts

arXiv:2609.10498v1 Announce Type: new Abstract: Recovering 3D human pose from monocular sports broadcasts remains challenging when players must be localized in a shared metric world coordinate system

Field-level prediction of mid-plane stress tensor fields in concrete target penetration: a cross-velocity graph neural operator surrogate

model-releasesarxiv-cs-lg

arXiv:2609.10032v1 Announce Type: new Abstract: Although the impact resistance of concrete has been studied extensively, a framework linking mesoscale heterogeneity to full-field stress-tensor predict

Field-level weak lensing cosmology with 60 simulations using multifidelity simulation-based inference

arXiv:2606.23346v2 Announce Type: replace-cross Abstract: We perform a realistic KiDS-Legacy mock analysis with field-level neural compression and simulation-based inference using just 60 N-body simul

FinCUABuild: Can Agents Build Reliable Benchmarks for Dynamic Financial Computer Use?

arXiv:2609.07603v1 Announce Type: new Abstract: Financial scenarios are diverse and complex, spanning varying data conditions, tool configurations, and workflows. Yet existing CUA, Computer-Using Agen

Fine PT-PT Web: A High-Quality 41 Billion Tokens Data Collection of the European Portuguese Web

arXiv:2609.07699v2 Announce Type: cross Abstract: Curating Web corpora for regional language variants like European Portuguese (PT-PT) is heavily bottlenecked by dialectal overlap (mainly with PT-BR)

applicationsarxiv-cs-ai

Fine-Tuning a KV Cache Concatenation-Aware Model or Recomputing KV Caches? Why Not Both?

model-releasesarxiv-cs-cl

arXiv:2609.09768v1 Announce Type: cross Abstract: In Retrieval-Augmented Generation (RAG) systems, a large number of retrieved chunks are concatenated to form the input context so that users can recei

Flawed but Memorable: Student Critical Reception of Interest-Personalized GenAI Analogies in Computing Education

arXiv:2609.06095v1 Announce Type: cross Abstract: Motivation: Undergraduate computing students increasingly turn to generative AI (GenAI) tools to understand abstract concepts through analogies. Analo

applicationsarxiv-cs-ai

FlowCPO: A Unified Divergence View of Preference Alignment for Flow Models

arXiv:2609.09905v1 Announce Type: cross Abstract: Preference alignment for flow and diffusion models now spans online reinforcement learning and offline preference optimization, but the relation betwe

safetyarxiv-cs-cv

FolDeX: A Physical-World Benchmark for Long-Horizon Robotic Manipulation of Deformable Objects

model-releasesarxiv-cs-ro

arXiv:2609.10243v1 Announce Type: new Abstract: Embodied AI, including vision-language-action and world-action models, must operate reliably in the physical world. Yet methods that perform well in sim

Forgetting Only What Matters: Layer-Selective Unlearning toward Robust LLMs

model-releasesarxiv-cs-lg

arXiv:2609.10439v1 Announce Type: new Abstract: Large Language Models (LLMs) can memorize and reproduce sensitive, copyrighted, or otherwise undesirable training content, creating privacy, safety, and

Forward-Free LLM Depth Pruning via Weight Redundancy

arXiv:2609.09883v1 Announce Type: new Abstract: Depth pruning reduces large language model (LLM) inference cost by removing complete Transformer blocks. Activation-based methods collect hidden states

researcharxiv-cs-lg

Local Ai

Frame-Coded Legged Locomotion over Noisy Terrain

arXiv:2609.10273v1 Announce Type: cross Abstract: Open-loop multilegged locomotion over rough terrain has been interpreted as matter transport over a noisy channel: leg-ground interactions are discret

local-aiarxiv-cs-ro

Freezing of Gait Prediction Under Spatial Occlusion: An IMU-Supervised Cross-Modal Distillation Approach

arXiv:2609.09826v1 Announce Type: new Abstract: Parkinson's disease is a progressive neurodegenerative disorder characterised by gradual deterioration of movement control. Automated freezing-of-gait (

applicationsarxiv-cs-cv

FreqBLiMP: Frequency-Controlled Minimal Pairs Reveal Robustness and Fragility of LLMs Under Lexical Rarity

arXiv:2609.07153v1 Announce Type: cross Abstract: Minimal-pair benchmarks such as BLiMP evaluate linguistic knowledge by testing whether language models (LMs) prefer acceptable sentences over minimall

FreqFLD: Towards All-in-One Facial Landmark Detection via Frequency Modulation

arXiv:2609.10278v1 Announce Type: new Abstract: Recent progress in deep learning has significantly advanced facial landmark detection. However, most existing methods process features in a spatial-doma

Frequency-Conditioned Flow Matching for Vision-Language-Action Models

arXiv:2609.10405v1 Announce Type: new Abstract: Robot actions are temporally correlated trajectories whose frequency components encode motion at different scales with highly non-uniform energy distrib

researcharxiv-cs-ro

Frequency Estimation Based on SNR-adaptive Frequency Estimator Under Wide SNR Range

arXiv:2609.07034v1 Announce Type: cross Abstract: Frequency estimation is the problem of estimating individual tone frequencies from noisy multi-tone sinusoidal signals. Existing frequency estimation

applicationsarxiv-cs-ai

Agents

FrogNano: Training a 4B Coding Agent via Online Task Synthesis

arXiv:2609.07925v2 Announce Type: new Abstract: We present FrogNano, a 4B coding agent designed to tackle software engineering (SWE) tasks efficiently and effectively, even under resource-constrained

agentsarxiv-cs-ai

Local Ai

From Citations to Contributions: LLM-Assisted Credit Scoring of Research Articles

arXiv:2609.07673v1 Announce Type: cross Abstract: Citation-based measures of scientific influence typically treat citations as uniform signals, ignoring the different roles that cited works play in a

local-aiarxiv-cs-ai

Local Ai

From Concentration to Differentiation and Back: Routing Effective Rank in MoE Reasoning Cohorts

arXiv:2609.06403v1 Announce Type: new Abstract: Test-time scaling produces cohorts of reasoning rollouts, yet there is no standard label-free account of how their internal computation reorganizes as i

local-aiarxiv-cs-ai

Agents

From Event Logs to Governed Action: A BlueSky Agenda for Agentic Process Mining

arXiv:2609.07984v1 Announce Type: new Abstract: Process mining has long turned event logs into process knowledge: discovered models, conformance evidence, bottleneck diagnoses, and runtime predictions

agentsarxiv-cs-ai

From Few-Shot Segmentation to Clinician-in-the-Loop Medical Image Analysis

arXiv:2609.10001v1 Announce Type: new Abstract: Few-shot medical image segmentation (FSMIS) seeks to delineate unseen structures from a small support set, but its standard formulation fixes task-defin

safetyarxiv-cs-cv

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

model-releasesarxiv-cs-cl

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 Landslide Conditioning Factors to Satellite Embeddings: Evaluating the Utilisation of Google AlphaEarth for Landslide Susceptibility Mapping using Deep Learning

arXiv:2601.07268v2 Announce Type: replace Abstract: Data-driven landslide susceptibility mapping (LSM) typically relies on landslide conditioning factors (LCFs), whose availability, heterogeneity, and

From Monolithic Blending to Agentic Orchestration: Dynamic Response for Conversational Assistants at Scale

arXiv:2609.05758v2 Announce Type: new Abstract: Conversational assistants can blend retrieval, action selection, escalation, and wording in a single model path, or separate those roles. We report a pr

safetyarxiv-cs-ai

From Pixels to Hierarchical Sequences: Quadtree Mask Encoding for Vision-Language Binary Change Detection

arXiv:2609.09876v1 Announce Type: new Abstract: Dense change detection in remote sensing requires vision-language models (VLMs) to compare bi-temporal images and generate accurate pixel-level masks. E

From Representation to Enactment: The ABC Framework of the Translating Mind

arXiv:2511.16811v2 Announce Type: replace Abstract: Building on the third-wave Extended Mind (EM) theory and radical enactivism, this article suggests an alternative to representation-based models of

researcharxiv-cs-cl

From Retrieval to Weights: Parametric Individualization of Small Language Models with Individual Text Corpora

arXiv:2609.10155v1 Announce Type: new Abstract: We approach a cognitive simulation perspective on episodic and semantic memory in multiple-choice question answering by incorporating text from individu

safetyarxiv-cs-cl

From Review to Authorization: Key-Isolated Threshold Signing for LLM Agents

arXiv:2609.05901v1 Announce Type: cross Abstract: Autonomous LLM agents can turn untrusted content into effectful actions such as payments and permission changes. If the same process interprets this c

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 Simulated Citizens to Simulated Deliberation: Challenges in Representation and Interaction

arXiv:2609.07573v1 Announce Type: new Abstract: Multi-agent LLM deliberation has been explored as a scalable way to simulate public deliberation. For such simulations to be informative, persona agents

safetyarxiv-cs-ai

Hardware

From Splats to Silicon: Rethinking Computational Efficiency of 3DGS

arXiv:2609.06157v1 Announce Type: cross Abstract: 3D Gaussian splatting (3DGS) represents scenes with explicit primitives and supports real-time novel-view synthesis, yet its system efficiency varies

hardwarearxiv-cs-ai

From Symbolic Perception to Logical Deduction: A Framework for Guiding Language Models in Geometric Reasoning

model-releasesarxiv-cs-cl

arXiv:2609.10335v1 Announce Type: cross Abstract: Plane geometry remains a significant challenge in AI, requiring the integration of visual perception and mathematical reasoning. While Large Multimoda