Search: “benchmark”

FAVoR: Measuring and Mitigating Author-Style Homogenization in Federated Personalized Generation

model-releasesarxiv-cs-cl

arXiv:2609.30968v1 Announce Type: new Abstract: Large language models are increasingly used as personalized writing assistants, but adapting a model across many authors can compromise individual writi

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FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting

DGX agent

arXiv:2512.14253v4 Announce Type: replace Abstract: In this work, we introduce FLAME, a family of extremely lightweight and capable Time Series Foundation Models, which support versatile forecasting t

safetyarxiv-cs-lg

28 Sept 2026

FlatClip: A Geometry-Aware Surface-Level Baseline for fMRI Representation Learning

arXiv:2609.31204v1 Announce Type: cross Abstract: Recent fMRI foundation models differ substantially in the spatial scale at which they represent brain activity. ROI- and connectivity-based models are

From ASR to ASP: Evaluating Prompt Attack Vulnerabilities Against Open-Source LLMs

model-releasesarxiv-cs-cl

arXiv:2505.14368v3 Announce Type: replace-cross Abstract: Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to attacks that generate harmful or sensitive outputs. As open-sou

From Reward Signal to Visual Utility: A Controlled Audit of Medical VLM Post-Training

arXiv:2609.31450v1 Announce Type: cross Abstract: Medical vision-language model (VLM) post-training is commonly evaluated through answer accuracy. We examine how changes in accuracy and training objec

From Weak Data to Strong Policy: Q-Targets Enable Provable In-Context Reinforcement Learning

arXiv:2609.30391v1 Announce Type: new Abstract: Existing in-context reinforcement learning methods mainly pretrain Transformers with supervised behavior-prediction objectives. This enables task infere

Game Arena: Strategic LLM Evaluation in Competitive Environments

arXiv:2609.31473v1 Announce Type: new Abstract: We introduce Kaggle Game Arena, an open and ever-expanding platform to evaluate large language models (LLMs) through competitive games. Different from s

researcharxiv-cs-ai

Geometric Inconsistency Localization in Multi-View Image Sets

arXiv:2609.31247v1 Announce Type: cross Abstract: Novel view synthesis (NVS) models can produce realistic new views of the same scene from different viewpoints. However, these generated views are not

GraphWrit3R: End-to-End 3D Scene Graph Writing

model-releasesarxiv-cs-cv

arXiv:2609.31595v1 Announce Type: new Abstract: 3D scene graphs provide a structured representation of complex environments by encoding objects, their semantic attributes, and the spatial and function

HuPER: A Human-Inspired Framework for Phonetic Perception

arXiv:2602.01634v2 Announce Type: replace-cross Abstract: We propose HuPER, a human-inspired framework that models phonetic perception as adaptive inference over acoustic-phonetics evidence and lingui

researcharxiv-cs-ai

HybridInfer: Thermal-Aware Reinforcement-Learning Tier Routing for On-Device, Edge, and Cloud LLM Inference

arXiv:2609.30270v1 Announce Type: new Abstract: On-device inference with small language models keeps user data local, works offline, and incurs no per-query cost, so the on-device tier is preferred wh

Tutorials

I Act Therefore I Am: When Is JEPA's Action-Conditioning Enough to Learn Causal Mechanisms?

arXiv:2609.31161v1 Announce Type: new Abstract: Recent empirical and theoretical advances suggest that joint-embedding predictive architectures (JEPAs) may learn meaningful representations for action-

tutorialsarxiv-cs-lg

IDM-Net: A Lightweight Illumination-Decoupled Modulation Network for Low-Light Image Enhancement

arXiv:2609.30962v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) remains challenging for lightweight models because illumination restoration and color fidelity are difficult to optim

Tutorials

Improving Molecular-Morphology Contrastive Pretraining using Deep-Learning-based Morphology Profiles

arXiv:2609.30433v1 Announce Type: new Abstract: Recent advancements in image-based profiling techniques have enabled the collection of high-volume cell morphology data, allowing new molecular embeddin

tutorialsarxiv-cs-lg

INTERACT: Interactive Planning for Autonomous Driving via Anchor-Conditioned Prediction and Trust-Region Refinement

model-releasesarxiv-cs-ro

arXiv:2609.31137v1 Announce Type: new Abstract: Driving in dense urban traffic is interactive: whether a merge or an unprotected turn succeeds depends on how surrounding agents respond to the ego vehi

Introducing FireRouter with Opus. Our first router model. Routine tasks go to top open models, Claude Opus handles the rest. Cache and task-…

model-releasesfireworks-ai--x

Introducing FireRouter with Opus. Our first router model. Routine tasks go to top open models, Claude Opus handles the rest. Cache and task-aware routing. Proven 98.1% of Opus accuracy with 57% lower

LAVOIR: Teaching a Single-Pass Decision Encoder When and What to Ask with Amortized Value of Information

arXiv:2609.30706v1 Announce Type: new Abstract: 'System One' decision models such as TypeSafe's Jev and its open counterpart Laya answer typed questions about a text in a single forward pass with cali

Learning Chance-Constrained MDPs with Bellman Distributional Certificates

arXiv:2609.30856v1 Announce Type: new Abstract: Safe reinforcement learning (RL) commonly enforces expected-cost constraints, but such expectation safety may fail to control the probability of rare hi

Learning Provable Neural Network Observer for Uncertain Dynamical Systems

arXiv:2609.30819v1 Announce Type: new Abstract: In many safety-critical applications, control of uncertain dynamical systems relies on observers that estimate states and external disturbances. Neural

Learning Robot Policies from Sparse Success Signals via STL-Guided Stein Variational Policy Gradient

arXiv:2609.31606v1 Announce Type: new Abstract: Learning robot policies for tasks with sparse success signals is challenging when completion depends on coordinated actions, precise contact outcomes, o

safetyarxiv-cs-ro

Learning to Bias: Machine Learning-Enhanced Particle Filters

arXiv:2609.30498v1 Announce Type: new Abstract: Sequential inference estimates latent states from noisy and incomplete observations. Particle Filters (PFs), a class of Monte Carlo methods based on imp

Learning to Stop without Learning to Stop: Self-Supervised Confidence Training Improves Reasoning Efficiency

arXiv:2609.31619v1 Announce Type: new Abstract: Reasoning models often generate very long reasoning traces, making inference computationally expensive. Existing approaches typically improve efficiency

Light Field Primitive for Novel View Synthesis

arXiv:2609.31198v1 Announce Type: new Abstract: We present Light Field Primitives (LFP), a formulation for novel view synthesis that replaces the dense ray database with a compact set of differentiabl

LLM Parkinsonism: Executive-Control Failure, Token-Inefficient Persistence, and an Uncertainty-Aware Global Executive Control Architecture for Autonomous Language-Model Agents

arXiv:2609.30662v1 Announce Type: new Abstract: Large language models (LLMs) can plan, use tools, write code, and execute long-horizon workflows, yet strong local competence does not guarantee project

ManiVid: Unified and Explainable Forensic Analysis of Manipulated Videos

arXiv:2609.30934v1 Announce Type: new Abstract: Rapid advances in AI-generated video (AIGV) have increased the risks posed by deceptive video manipulation. Unlike fully synthetic videos, manipulated v

MDSkin-Net: Multi-Task Skin Lesion Analysis Driven by Pattern Analysis Priors and Spatial Alignment Regularization

model-releasesarxiv-cs-cv

arXiv:2609.30855v1 Announce Type: new Abstract: Reliable skin lesion segmentation and classification are central to dermoscopic computer-aided diagnosis. Existing multi-task frameworks couple the two

Mechanism-Aware Ensemble Conditioning for Data-Limited Emulation of Extreme Events

arXiv:2609.30746v1 Announce Type: new Abstract: Extreme events in chaotic systems are difficult to learn from short trajectories because they are controlled by transient finite-time instability rather

MeshGraphNet-Transformer: Scalable Mesh-based Learned Simulation for Solid Mechanics

arXiv:2601.23177v4 Announce Type: replace Abstract: We present MeshGraphNet-Transformer (MGN-T), a novel architecture that combines the global modeling capabilities of Transformers with the geometric

MM-VeriAgent: Learning to Use Extensive Tools to Verify Multimodal Misinformation with Reinforcement Learning

arXiv:2609.30698v1 Announce Type: new Abstract: Real-world multimodal misinformation often involves mixed forgery sources, requiring sample-specific detection strategies. Existing tool-augmented metho

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Models Got Talent: Identifying High Performing Wearable Human Activity Recognition Models Without Training

arXiv:2511.06157v3 Announce Type: replace-cross Abstract: Discovering high performing model architectures for wearables-based Human Activity Recognition (HAR) applications is challenging. The astonish

Multi-agent Scaling Across Disjunctive and Compensatory Tasks

arXiv:2609.31563v1 Announce Type: new Abstract: Multi-agent LLM systems are often expected to improve as team size increases, yet the scaling behavior may depend on task structure. Our central contrib

NEMSim: Learning Control-Conditioned Multi-Event Physical Dynamics via Executable Event-Mechanism Priors

arXiv:2609.30718v1 Announce Type: new Abstract: High-fidelity simulation of control-conditioned multi-event physical systems is computationally expensive, especially across broad control spaces and lo

New LoRA Skills Should Read but Never Write

arXiv:2609.31600v1 Announce Type: new Abstract: Low-rank adapters (LoRA) make it cheap to fine-tune a large language model once per task, but combining several independently trained adapters into one

NEXT: Physics-Informed Neuro-Spectral Exponential Time Differencing Architectures

arXiv:2609.31539v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) build neural representations of time-dependent PDE solutions, naturally incorporating physics knowledge and obs

Nice Fold or Hero Call: Learning Budget-Efficient Thinking under Policy-Dependent Solvability

arXiv:2605.11625v2 Announce Type: replace Abstract: Large reasoning models (LRMs) improve problem solving through extended reasoning, but often misallocate test-time compute. Existing efficiency metho

Offline Policy Evaluation as a decision support tool for designing Adaptive Experiments

arXiv:2609.30273v1 Announce Type: new Abstract: We investigate how historical data from fixed randomized experiments (A/B tests) can be used to inform the deployment of adaptive experiments based on c

ORCA: Evaluating LLMs on Data Science Code Translation

arXiv:2609.30749v1 Announce Type: new Abstract: Data Science Code Translation (DSCT) is the process of converting code between data science libraries while preserving functional equivalence and enabli

OSPO: Object-Centric Self-Improving Preference Optimization for Text-to-Image Generation

arXiv:2506.02015v4 Announce Type: replace Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have enabled unified multimodal understanding and generation. However, they still strugg

safetyarxiv-cs-cv

Persistent Homology of Time Series through Complex Networks

arXiv:2605.01624v1 Announce Type: cross Abstract: We present a unified pipeline for univariate time series classification via complex networks and persistent homology. A time series is mapped to a gra

researcharxiv-cs-lg

Persistent Negatives for Adversarial Black-Box On-Policy Distillation

arXiv:2609.30864v1 Announce Type: cross Abstract: Black-box On-Policy Distillation (OPD) seeks to improve a student from its own generations when the teacher provides sampled responses but not token p

Applications

PhoenixSR: Generative Heterogeneous Distillation Unleashes Efficient Models for Real-World Super-Resolution

arXiv:2609.30988v1 Announce Type: new Abstract: Real-world image super-resolution (SR) requires recovering perceptually realistic high-resolution images from complex low-resolution observations while

applicationsarxiv-cs-cv

PICO: Projection-Informed Consistency Optimisation for 6DoF Surgical Tool Pose Estimation

arXiv:2609.30989v1 Announce Type: new Abstract: Purpose: Accurate 6 DoF pose estimation of surgical tools is critical for automa- tion, robotic proprioception, and safe interaction with the tissue ope

Preserve-and-Compose Training for Composed Image Retrieval

arXiv:2609.31202v1 Announce Type: new Abstract: Composed image retrieval (CIR) aims to retrieve images that satisfy a user-specified modification while preserving relevant visual content from a refere

ProCAP: Probabilistic Cross-Attentive Prompt Learning for Vision-Language Models

arXiv:2609.30434v1 Announce Type: new Abstract: Pre-trained vision-language models such as CLIP can recognize new categories via prompting, but they often struggle when labeled data are scarce or the

Quadruped Obstacle Avoidance and Footstep Planning with Distributed Low-cost Time-of-Flight Sensors

arXiv:2609.31008v1 Announce Type: new Abstract: Quadruped robots typically rely on depth cameras and LiDAR sensors to map their local environment. However, these sensors have limited close-range cover

researcharxiv-cs-ro

Quantum Diffusion Models for Medical Image Analysis

arXiv:2609.31070v1 Announce Type: cross Abstract: Quantum Machine Learning is a novel field of research aimed at devising machine learning approaches exploiting principles of quantum mechanics, such a

Query-Conditioned Prototype Adaptation for Cross-Domain Few-Shot Learning: Single-Query Inference, Controlled Comparisons, and Failure Modes

model-releasesarxiv-cs-cv

arXiv:2609.30769v1 Announce Type: new Abstract: Cross-domain few-shot learning requires adapting a classifier to a new visual domain from very few labelled examples without target-time parameter updat

RAZOR: Pruning Replaceable Experts in LLMs

model-releasesarxiv-cs-cl

arXiv:2609.30465v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models activate few experts per token but store the full expert pool. Expert pruning reduces this storage burden; at a fixed