Search: “model-releases”

AuthBench: A Large-Scale Multilingual Benchmark for Authorship Representation across Genres and Lengths

arXiv:2609.06771v1 Announce Type: cross Abstract: Authorship signals matter in settings where writing style carries identity: digital forensics, plagiarism analysis, account linking, misinformation in

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Model Releases

AutoFyn Technical Report: Non-Parametric Expert Iteration for Long-Horizon Agents

DGX agent

arXiv:2609.05446v1 Announce Type: new Abstract: We introduce AutoFyn, an agent harness inspired by the Expert Iteration algorithm, adapting a frozen model across many rounds by updating persistent sta

model-releasesarxiv-cs-ai

10 Sept 2026

Automated Design of Inventory Policy with Large Language Models: An Exploratory Study

arXiv:2609.08071v1 Announce Type: new Abstract: Firms making inventory decisions have access to operational data, optimization tools, and large language models (LLMs). Typically, data characterize the

Automatic Reproducible Camera Intrinsic Calibration

arXiv:2609.10082v1 Announce Type: cross Abstract: Accurate camera intrinsic calibration is fundamental to robot perception, and the accuracy depends on the quality of the collected images. However, ex

AVSRBench: A Multi-Condition AVSR Benchmark

arXiv:2609.10366v1 Announce Type: cross Abstract: While AVSR has achieved sub-1% word error rates on the standard LRS3 benchmark, its reliance on broadcast speech obscures whether this reflects true g

Behavioral Grammar: Detecting Adaptive Malware via Tiny Language Model Priors and Second-Order Temporal Analysis

arXiv:2608.00745v2 Announce Type: replace Abstract: Modern endpoint detection systems face a fundamental tension: signature-based approaches are trivially evaded by polymorphic or adaptive threats, wh

Benchmark Scores Are Pipeline-Dependent: A Reliability Audit of Cybersecurity LLM Benchmarks

arXiv:2609.08765v1 Announce Type: cross Abstract: Large language model (LLM) benchmarks are often treated as fixed datasets with stable scores, yet their outcomes depend on configurable evaluation pip

Benchmarking Hybrid Deep Research Across Database Querying and Web Search

arXiv:2609.09410v1 Announce Type: new Abstract: While autonomous agents have made significant strides in 'deep research' by iteratively navigating the open web to synthesize information, real-world pr

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 Coherence: Benchmarking Professional Editing-Technique Execution in Multi-Shot Audio-Video Generation

arXiv:2609.08275v1 Announce Type: new Abstract: Recent multi-shot audio-video generators can produce increasingly coherent and cinematic outputs, but coherence does not imply the ability to execute ed

Beyond Conventional Federated Learning via High-Order Regularization

arXiv:2609.09904v1 Announce Type: new Abstract: Federated clients that perform several local optimization steps can return parameter displacements with widely different magnitudes. The quadratic regul

Beyond Cross-Lingual Transfer: Benchmarking Propagation Boundaries in Multilingual LLM Unlearning

arXiv:2609.05976v1 Announce Type: cross Abstract: Large Language Model (LLM) unlearning aims to suppress target knowledge while preserving general capabilities. In multilingual settings, unlearning mu

Beyond Final Decisions: A Process-Centric Benchmark for Transparent AI-Assisted Peer Review

arXiv:2609.05947v1 Announce Type: new Abstract: Peer review is central to quality control in science. However, existing evaluations of AI-assisted peer review mainly focus on the overall quality of ge

Beyond One-Size-Fits-All: Sample-Adaptive Strategy Routing for Vision Token Pruning in MLLMs

arXiv:2609.10346v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) process hundreds or thousands of visual tokens per image, incurring prohibitive inference costs. While existing

Beyond Sparse Rewards: A New Benchmark and Structure-Aware Graph Alignment for Micro-Drama Understanding

arXiv:2609.07107v1 Announce Type: new Abstract: Micro-dramas, characterized by ultra-short durations and hyper-dense storylines, pose unique challenges for video understanding that conventional benchm

Beyond Top-k Skill Retrieval: Diversity-Aware Skill Routing for LLM Agents

arXiv:2609.05824v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on external skills, but routing user requests over large skill registries is difficult because many

Beyond Top Words: MonoTM for Topic Modeling with Interpretable Monosemantic Features

arXiv:2609.09575v1 Announce Type: new Abstract: Topic models summarize large text corpora, but top-ranked words often provide only a limited representation of topic semantics. Sparse autoencoders (SAE

Building the Harness Automatically: Self-Play in Code Distills a Text Harness for Black-Box Optimization

arXiv:2609.09468v1 Announce Type: new Abstract: Can an agent learn a numerical search strategy through executable practice and then transfer that strategy as text? We study low-budget black-box optimi

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

Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization

arXiv:2609.10410v1 Announce Type: new Abstract: The growing complexity of content moderation policies presents a critical challenge for their consistent operationalization. While foundation models pos

Can We Trust Video Hallucination Detectors? VidHalLoc for Evaluating the Evaluators

arXiv:2609.09895v1 Announce Type: new Abstract: Video-language models and video agents can produce hallucinations that conflict with spatiotemporal evidence. Existing benchmarks mainly evaluate model

Candor-LR: A Dyadic Conversational Dataset for Audio-Visual Speech Recognition

arXiv:2609.10394v1 Announce Type: cross Abstract: Current audio-visual speech recognition (AVSR) benchmarks, like LRS3, rely heavily on clean, scripted and rehearsed speech. They fail to reflect the c

CausalVerify: An Execution-Grounded Benchmark for LLM Causal Inference Workflows

arXiv:2609.07944v1 Announce Type: new Abstract: Existing causal-inference benchmarks for LLMs mostly score method descriptions or whether generated code runs, not whether the executed workflow recover

Characterizing Contention-Induced Reliability Collapse in KV-Cache Timing Side Channels for Multi-Tenant LLM Serving

arXiv:2609.06853v1 Announce Type: cross Abstract: Shared key--value (KV) cache reuse improves large language model (LLM) serving, but it can also create a timing side channel that reveals whether a pr

CHIMERA Challenge Task 2 and 3: Response Subtypes Classification and Progression Survival Prediction in Bladder Cancer Patients using Multimodal Datasets

arXiv:2609.09510v1 Announce Type: cross Abstract: High-risk non-muscle-invasive bladder cancer (HR-NMIBC) carries substantial risks of recurrence and progression, while current clinical risk stratific

CIPHER: Benchmarking Cross-record Inference over Privacy-Hardened Evidence Records

arXiv:2609.07022v1 Announce Type: cross Abstract: Reasoning over privacy-constrained records requires combining structured attributes with evidence from free-text narratives. We introduce CIPHER (Cros

CityPlanner: A Sandbox Agent for Executable Urban Planning

arXiv:2609.09578v1 Announce Type: cross Abstract: Urban planning is a real-world spatial optimization problem that requires selecting feasible actions from large candidate spaces under practical objec

CIVI: A Framework for Diagnosing Search Agent Failures in Civic Information

arXiv:2609.08094v1 Announce Type: new Abstract: Large Language Models are increasingly deployed in public-sector settings, where incorrect guidance can cause irreversible harm. We introduce CIVI, the

Climate-ModernBERT: Revisiting Corpus Composition for Domain-Adaptive Continued Pretraining

arXiv:2609.07798v1 Announce Type: cross Abstract: Natural Language Processing (NLP) in the climate domain requires models to process heterogeneous text sources, including scientific literature, policy

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

Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails

arXiv:2609.09134v1 Announce Type: new Abstract: Agent harnesses (the system prompt, tool set, execution hooks, and context-management scaffolding around a model) are a critical determinant of agentic

Complexity and Scale in AI-Assisted Workflow Management: A Federated Learning Case Study

arXiv:2606.18425v2 Announce Type: replace-cross Abstract: Federated learning over medical images is a demanding workflow application. Each round fans out across parallel client jobs and converges on a

ConsistencyAI: A Benchmark to Assess LLMs' Factual Consistency When Responding to Different Demographic Groups

arXiv:2510.13852v3 Announce Type: replace-cross Abstract: Is an LLM telling you different facts than it's telling me? This paper introduces ConsistencyAI, an independent benchmark for measuring the fa

Contrastive Projection: Reading Transformer Internals by Differencing Logit Lenses

arXiv:2609.09902v1 Announce Type: new Abstract: Reading a transformer's internal states in token space is easy to do and hard to trust: a logit lens on a single hidden state is dominated, at intermedi

Copying explains the collective behavior of AI agents in the wild

arXiv:2609.09150v2 Announce Type: replace-cross Abstract: In June 2026, thousands of AI agents found that a small public wiki would accept edits from inside their sandboxes, and started using it to he

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

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

CWF: A Collaborative Writing Framework for Personalized and Reliable Popular Science Writing

arXiv:2609.06126v1 Announce Type: new Abstract: We introduce Personalized and Reliable Popular Science Writing, a novel task that requires adapting scientific explanations to audiences with different

DAREBench: Deployment-Aware and Reliable Evaluation of Models as Agents

arXiv:2609.06059v1 Announce Type: new Abstract: As large language models evolve from question-answering systems into general-purpose agents, evaluation must move beyond static answer correctness to as

DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registration

arXiv:2509.06285v2 Announce Type: cross Abstract: LiDAR point cloud registration is fundamental to robotic perception and navigation. In geometrically degenerate environments (e.g., corridors), regist

Decision-Focused Active Learning for Scale-Aware Critical-Materials Recovery

model-releasesarxiv-cs-ro

arXiv:2609.09413v1 Announce Type: cross Abstract: Choosing a recovery process for scale-up requires connecting laboratory results with product requirements, process costs, and scale effects. We analyz

Deep Learning-Based Detection of Electrical Faults and Power Quality Disturbances in Aerospace Power Systems

arXiv:2609.10479v1 Announce Type: cross Abstract: More Electric Aircraft require fast and reliable monitoring of high-frequency electrical networks, yet most power quality disturbance and fault diagno

Deep Neural Networks for Learning Intent from sEMG Signals to Support Hardware Devices for Post-Stroke Neurorehabilitation

arXiv:2609.09971v1 Announce Type: new Abstract: Finger-specific motor intent is a clinically meaningful control signal for post-stroke neurorehabilitation, where residual muscle activity may remain me

Deformable Object Manipulation under Partial Observability via Real-Time Full-Shape Estimation

model-releasesarxiv-cs-ro

arXiv:2609.10308v1 Announce Type: new Abstract: Manipulating deformable objects (DOs) is challenging due to their high-dimensional state space, underactuated dynamics, and partial observability. In th

Development and Validation of a Physics-Guided Machine Learning Extrapolation Framework Using a Classical Transient Diffusion Benchmark

arXiv:2609.09912v1 Announce Type: new Abstract: Machine learning models used in engineering are typically trained within limited operating ranges, yet reliable predictions are often required beyond th

DI-Bench: Systematically Generating In-Domain Data Intelligence Benchmarks for Enterprise Agents

arXiv:2609.05776v1 Announce Type: new Abstract: Evaluating enterprise agents on domain-specific benchmarks is critical, yet public benchmarks rarely evaluate whether agents can integrate business know

Diffs vs. Whole Files: An Empirical Comparison of Iterative Edit-Based and Direct Generation for Flutter/Dart Code Models

arXiv:2609.05779v1 Announce Type: cross Abstract: Large language models used for code editing can be trained and deployed in at least two output regimes: direct generation, where the model emits the e

Do Dynamic Routers Need Memory? HeRo: History-Aware Routing for Efficient LLM Inference

arXiv:2609.08189v1 Announce Type: new Abstract: Dynamic layer routing reduces the inference cost of Large Language Models (LLMs) by learning to skip layers for individual tokens. Existing methods, how

Do Large Language Models Know What They Don't Know II? A Fully Behavioral, Non-Cognitive Measure of Epistemic Honesty

arXiv:2609.07879v1 Announce Type: new Abstract: Large Language Models (LLMs) are frequently confident, eloquent, and well versed. A natural question arises: do they know what they don't know? To answe