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EnComp: Lightweight Encoder-Only Context Compression for Retrieval-Augmented Question Answering

arXiv:2603.09222v2 Announce Type: replace Abstract: Efficient context compression is critical for retrieval-augmented question answering in resource-constrained settings, where long retrieved contexts

researcharxiv-cs-cl

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Energy-guided Recursive Model

DGX agent

arXiv:2607.10128v3 Announce Type: replace Abstract: Recursive models show promise on reasoning and language tasks, yet their test-time scaling lacks a principled criterion for selecting trajectories o

local-aiarxiv-cs-lg

24 Sept 2026

Enhancing Multiclass Malware Classification in Resource-Constrained Environments

arXiv:2609.27950v1 Announce Type: cross Abstract: The emergence of multi-class malware attacks such as ransomware, spyware, trojans, etc., presents an increasing and serious threat to cybersecurity, p

researcharxiv-cs-lg

Enhancing Small Language Models for Power Outage Report Generation via Minimum Risk Training

arXiv:2609.27197v1 Announce Type: new Abstract: Minimum Risk Training (MRT) enables neural machine translation models to directly optimize sequence-level evaluation metrics instead of relying only on

EnSIMem: Entity-Structured Indexing for Long-Term Agent Memory

arXiv:2609.27279v1 Announce Type: new Abstract: An agent that interacts with users over long periods must recall facts, preferences, events, and changes from a continuously growing interaction history

agentsarxiv-cs-ai

Escaping Python Dependency Hell: A Hybrid Replay-and-Repair Pipeline for Python Dependency Resolution

arXiv:2609.26952v1 Announce Type: new Abstract: Dependency conflicts in Python ecosystems arise from incompatible version constraints, missing packages, and undocumented compatibility relationships, c

Evaluating ADC-only deep learning pipelines for breast cancer detection and segmentation using standalone diffusion-weighted MRI

arXiv:2609.27815v1 Announce Type: cross Abstract: Dynamic contrast-enhanced (DCE) imaging is the gold standard technique for the detection and characterization of breast cancer using magnetic resonanc

Evaluating Feedback Focus and Pedagogical Adaptivity in LLM-Generated Feedback on Student Writing

arXiv:2609.28026v1 Announce Type: cross Abstract: We investigate whether state-of-the-art large language models (LLMs) generate feedback that reflects the pedagogical practices of expert teachers in t

Evaluating Open-Weight LLMs for Turkish Domain Documents Under Retrieval and Hardware Constraints

arXiv:2609.28007v1 Announce Type: new Abstract: Most Turkish-capable large language models (LLMs) are evaluated using general-purpose benchmarks rather than long, structurally complex domain documents

Evaluation Choices Decide the Forecasting Leaderboard: Evidence from a Production Marketplace Panel

arXiv:2609.27867v1 Announce Type: new Abstract: A forecasting benchmark reports which method won. We show that the answer is set by the evaluator's choices before any model is fitted. We benchmark 24

Evaluation of pre-trained models for pedagogical assessment of novel AI-assisted educational questions

arXiv:2609.27749v1 Announce Type: new Abstract: The surge in AI-assisted generation of educational materials has outpaced our capacity to validate their pedagogical quality. Automated evaluation using

EvEMTBench: An Open Benchmark for Machine Learning in Power System Protection

arXiv:2609.28149v1 Announce Type: cross Abstract: Studies of machine-learning-based power system protection are difficult to compare because task definitions, measurement access, data partitions, metr

Even Sharper Bounds for Transductive Learning and Its Applications

arXiv:2609.28459v1 Announce Type: new Abstract: We introduce Sharper Transductive Local Complexity (STLC), a localized complexity method for transductive learning under uniform sampling without replac

EviStreams: Human-in-the-Loop AI Data Extraction for Systematic Reviews in Medicine

arXiv:2609.27418v1 Announce Type: new Abstract: Systematic reviews underpin clinical guidelines, yet their data-extraction step is a major expert-labor bottleneck bound by a protocolized workflow: two

EvoAudio: Recursive Self-Improvement for Audio Understanding

arXiv:2609.27389v1 Announce Type: cross Abstract: Audio language models understand what is said far better than how it sounds. Closing this gap takes more than data. Detailed acoustic annotation is co

researcharxiv-cs-lg

Evolutionary Stability Does Not Guarantee Learning Accessibility: A Multi-Agent Reinforcement Learning Perspective on Cooperation Emergence

arXiv:2609.27664v1 Announce Type: new Abstract: Cooperation emergence is a central problem in multi-agent systems because decentralized agents must coordinate while adapting to the changing behavior o

agentsarxiv-cs-ai

Evolving Inspectable O-RAN Slicing xApps with LLMs

arXiv:2609.27337v1 Announce Type: cross Abstract: Open RAN (O-RAN) slicing xApps must adapt resource allocations to changing channel conditions and traffic demands while meeting service-level agreemen

Exact Feedback Is Not Control: Evaluating Text-based Closed-Loop Revision in LLMs

arXiv:2609.28150v1 Announce Type: new Abstract: Closed-loop revision is increasingly used in large language model (LLM) applications, but failures may reflect incomplete feedback or ineffective respon

researcharxiv-cs-cl

Exact Minimax One-Bit Unbiased Compression: Heavy-Tail Necessity and Finite-Randomness Approximation

arXiv:2609.27860v1 Announce Type: new Abstract: A pointwise-unbiased one-bit compressor reconstructs every real input in expectation while transmitting one bit. For a scalar source P with CDF F, mean

Exact Quantile Balancing and Load-Error Injection for Mixture-of-Experts

arXiv:2609.28053v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) training requires global load balance to prevent expert under-utilization and local balance for efficient expert-parallel exe

Experts Rise Where LLMs Disagree: Using Cross-Model Disagreement to Target Expert Effort in LLM Codebook Revision for Large-Scale Annotation

arXiv:2609.26926v1 Announce Type: cross Abstract: Large-scale text annotation brings expert insight to millions of documents, often through a codebook that AI annotators follow. Developing a robust co

FairTest: Search-Based Fairness Testing for Multi-Agent Reinforcement Learning Systems

arXiv:2609.27309v1 Announce Type: cross Abstract: Multi-agent Reinforcement Learning (MARL) trains a team of agents that share one environment and learn their policies together. Training maximizes the

Faithful, Interpretable Chest X-ray Diagnosis with Artifact-free B-cos Networks

arXiv:2507.16761v3 Announce Type: replace Abstract: Faithfulness and interpretability are essential for deploying deep neural networks (DNNs) in safety-critical domains such as medical image analysis.

safetyarxiv-cs-cv

False-science induction in autonomous scientific discovery

arXiv:2609.27883v1 Announce Type: cross Abstract: Closed-loop discovery systems increasingly execute experiments and update decisions autonomously, turning record integrity into part of the experiment

agentsarxiv-cs-ai

Fast Direction-Conditioned Reachability for Motion Prediction Under Model Uncertainty

arXiv:2609.27077v1 Announce Type: new Abstract: To avoid collisions, a robot must repeatedly predict where nearby agents may move, usually with an imperfect model of their dynamics. Reachable sets pro

agentsarxiv-cs-ro

FastManly: An EM-Gradient Algorithm for Manly Mixture Models

arXiv:2410.00848v2 Announce Type: replace-cross Abstract: A faster implementation of mixtures of Manly transformations is proposed. This method, called FastManly, uses Newton's method for optimization

researcharxiv-cs-lg

FDE-Bench: Evaluating LLM Agents for Deployment Environment Configuration

arXiv:2609.27571v1 Announce Type: cross Abstract: Deployment requires an agent to turn application code into a running system whose services connect, become ready, and remain observable. FDE-Bench eva

Fed-ReMasker: Federated Tabular Imputation under Feature-Level Missingness

arXiv:2609.28105v1 Announce Type: cross Abstract: Multi-center clinical studies and biomedical research collaborations increasingly seek to utilize data across centers to build models that generalize

FedIncome: Federated Learning for Income Estimation in Digital Lending Under Data Sovereignty Constraints

arXiv:2609.27654v1 Announce Type: cross Abstract: Verified income is often unavailable in digital loan applications, forcing lenders to rely on reported income and potentially leading to over-lending,

Feed the Panel Dimensions, Not Verdicts: Rubric-Decomposed Fusion of Vision-Language Aesthetic Judges

arXiv:2609.27110v1 Announce Type: cross Abstract: Vision-language models (VLMs) are deployed as zero-shot judges of image aesthetics, and panels of several models are recommended, on thin evidence, as

researcharxiv-cs-cl

FFM-CP: Cross-Backbone Fusion of Vision-Language Foundation Models for Few-Shot Computational Pathology

arXiv:2609.27710v1 Announce Type: new Abstract: Pathology vision-language foundation models vary in performance across diseases and tasks, with no single model consistently performing best. The high c

safetyarxiv-cs-cv

Field-of-View Extension in Dental Cone-Beam CT via Implicit Neural Representations and Diffusion Model-Based Refinement

arXiv:2609.28110v1 Announce Type: cross Abstract: Dental cone-beam computed tomography (CBCT) systems often employ detector configurations that provide a truncated field of view (FOV) that only captur

Fine-Tune, Then Rectify

arXiv:2511.19486v3 Announce Type: replace-cross Abstract: Driven by recent advances in artificial intelligence, a growing literature has demonstrated the potential of using large language models (LLMs

Fine-Tuning LLMs for Translation: General Forgetting Mitigation Does Not Preserve MT-Specific Instruction Following

arXiv:2609.28395v1 Announce Type: new Abstract: Fine-tuning large language models on parallel data improves translation quality but can cause catastrophic forgetting. Mitigation methods are generally

Fine Wrist Control as a Marker of Surgical Teleoperation Expertise

arXiv:2609.27160v1 Announce Type: new Abstract: Unlike most intensely physical pursuits, surgical robotic teleoperation training focuses primarily on task outcomes rather than surgeon body posture or

researcharxiv-cs-ro

Finite-Sample Probabilistic Safety Certification for AI-Based Grid-Edge Coordination

arXiv:2609.28182v1 Announce Type: new Abstract: Coordinating large population of flexible grid-edge devices can alleviate the need for time-consuming and capital-intensive network upgrades, and AI-bas

safetyarxiv-cs-ai

FLEET: From Logits Entropy to Enhanced Trajectories in Text Generation

arXiv:2609.27657v1 Announce Type: cross Abstract: Solutions based on large language models (LLMs) often rely on temperature sampling to improve accuracy and stability by aggregating multiple samples f

FLINT: Fast Lightweight Inference for Traversability

arXiv:2609.26857v1 Announce Type: cross Abstract: Navigation in off-road conditions is challenging due to the lack of structure. There is no fixed vocabulary for what is traversable. The traversabilit

Forecast Workflow Bench: Evaluating Language-Model Decisions with Budgeted Forecast Tools

arXiv:2609.27385v1 Announce Type: cross Abstract: Time-series foundation models (TSFMs) provide forecasts for operational decisions, but accuracy alone does not determine their value. Evaluating agent

Forget who you Forgot: Speaker Unlearning to Prevent Re-Identification in Zero-Shot Text-to-Speech

arXiv:2609.27399v1 Announce Type: cross Abstract: Recent zero-shot text-to-speech (ZS-TTS) systems can reproduce a speaker's voice with high fidelity from only a few seconds of reference speech, raisi

ForgetMimic: Motion Unlearning for Reinforcement Learning Humanoid Control

arXiv:2609.28378v1 Announce Type: cross Abstract: Humanoid control, leveraging human demonstrations, has achieved diverse, agile, and natural locomotion behaviors through reinforcement learning (RL).

From Agent Output to Authorized Transition

arXiv:2609.28216v1 Announce Type: cross Abstract: Agentic engineering systems can edit repositories, run tools and tests, build firmware, synthesize schematics, and prepare deployable or manufacturabl

safetyarxiv-cs-ai

From Alignment to Fusion in 3D Vision-Language

arXiv:2609.28222v1 Announce Type: new Abstract: Unified 3D vision-language systems must combine complementary geometry, scale, and appearance cues while supporting tasks from instance segmentation to

safetyarxiv-cs-cv

Tutorials

From Change Captions to Change Detection: Semantic-Appearance Agreement Framework for Remote Sensing Change Detection

arXiv:2609.28192v1 Announce Type: new Abstract: Remote sensing change detection (RSCD) is essential for monitoring land-cover changes and urban development. However, most methods demand pixel-level ch

tutorialsarxiv-cs-cv

From ECG Signals to Representative-Morphology Heatmaps for Biometric Recognition

arXiv:2609.28183v1 Announce Type: new Abstract: Electrocardiography (ECG) contains subject-specific morphology that supports biometric recognition, yet image-based performance depends on how the wavef

researcharxiv-cs-cv

Local Ai

From greenhouse climate to individual leaves: an organ-resolved model of lettuce growth

arXiv:2609.27118v1 Announce Type: new Abstract: Greenhouse climate management aims to improve crop production while limiting energy use. This requires knowing how a crop will respond before conditions

local-aiarxiv-cs-cv

From LiDAR Maps to Visual Localization: Unified Visual Association for Robust Point-Line-Plane Pose Estimation

model-releasesarxiv-cs-ro

arXiv:2609.27363v1 Announce Type: new Abstract: Camera localization in a prior LiDAR map provides a persistent geometric reference for long-term robotic navigation, yet remains challenging because of

From Reasoning Strings to Partial Orders: Verifier-Certified Rule Transport through Quotient Policy Optimization

arXiv:2609.27833v1 Announce Type: new Abstract: Many computations admit several valid execution orders because independent subgoals or disjoint state updates can commute. Reinforcement learning with v