Search: “model-releases”

Identifying Representational Biases in Datasets Using PCA: A Max-Disparity Partition Framework

arXiv:2609.24556v1 Announce Type: cross Abstract: Principal Component Analysis (PCA) minimises aggregate reconstruction error, which can inadvertently represent majority subgroups with substantially h

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Model Releases

IMPLICIT-Bench: Measuring Implicit Bias in Text-to-Image Models under Neutral Prompts

DGX agent

arXiv:2609.24228v1 Announce Type: new Abstract: Text-to-image (T2I) models are typically evaluated for bias using slot-based templates such as ``a photo of a [profession]''. Such templates probe only

model-releasesarxiv-cs-cv

22 Sept 2026

Improved Private Sparse Covariance Estimation with Multiscale Threshold Tests

arXiv:2609.22783v1 Announce Type: new Abstract: We study differentially private covariance estimation in operator norm for mean-zero sub-Gaussian distributions with unknown covariance support and at m

Improving Parameter Utilization by Sharing Neural Experts Across Layers in Transformers

arXiv:2609.22199v1 Announce Type: new Abstract: Transformer-based large language models often suffer from inter-layer parameter redundancy, where functional transformations are redundantly learned acr

Information-Directed Sampling for Causal Bandits

arXiv:2607.15577v2 Announce Type: replace Abstract: Causal bandits exploit structural relationships among variables to share information across interventions and accelerate the identification of high-

InsertAnything: Generalizable Contact-Rich Precision Insertion from Simulation to Reality

arXiv:2609.24511v1 Announce Type: new Abstract: Contact-rich precision insertion is a key manipulation skill in robotic assembly. Tight clearances make insertion more sensitive to alignment errors and

Is Imagination Derived from Hallucination? A Cross-Taxonomy Evaluation of Imagination and Hallucination in Large Language Models

arXiv:2609.22152v1 Announce Type: new Abstract: Imagination performs as a high-level function of large language models (LLMs) which determines the potential of how an LLM creates unseen or creative co

iSDFT: Information-Proximal Self-Distillation for Continual Learning in LLMs

arXiv:2609.24646v1 Announce Type: new Abstract: On-policy self-distillation fine-tuning (SDFT) learns new skills from demonstrations while reducing forgetting, but it always distils toward the full de

ITSY: Causal Discovery From Irregular Time-Series Data

arXiv:2609.23516v1 Announce Type: new Abstract: Structural causal models for time series recover contemporaneous and lagged effects, but most methods require complete observation windows and become mi

JAREX: An Acquisition Function for Multi-Objective Algorithmic Process Characterization

arXiv:2609.24954v1 Announce Type: cross Abstract: Pharmaceutical process characterization is central to Quality by Design because it defines how variations in process parameters affect the ability to

K-TRAIL: Simulator-Guided Generative Design of EM/RF Circuits

arXiv:2609.23183v1 Announce Type: new Abstract: Inverse design of RF and electromagnetic (EM) circuits is challenging because the relationship between circuit layout and electrical response is non-uni

Knowing When to Trust Images: Reliability-Aware Multi-modal Entity Alignment

arXiv:2609.23267v1 Announce Type: new Abstract: The visual modality, i.e., images, plays a key role in multi-modal entity alignment (MMEA). Existing approaches often directly fuse the image with other

LD-RSVIS: A Large-Scale and Diverse Benchmark for Referring Surgical Video Instrument Segmentation

arXiv:2609.23067v1 Announce Type: new Abstract: Referring surgical video instrument segmentation (RSVIS) aims at segmenting the instrument in a surgical video, given a textual description. Despite rec

Leakage-Safe Empirical Benchmarking of EEG-Based Machine Learning Pipelines for Dementia Classification

arXiv:2609.22092v1 Announce Type: cross Abstract: Electroencephalography (EEG) is a low-cost and non-invasive signal source for dementia screening, yet existing EEG-based studies remain difficult to c

Learning and Control Beyond Linearity: Towards a Non-asymptotic Theory for Bilinear Systems

arXiv:2609.22338v1 Announce Type: cross Abstract: This tutorial provides a unified view of the emerging area of bilinear learning and control. Using linear systems as a benchmark, it explains what fun

Learning Physics from an Imperfect Ancestor

arXiv:2609.24947v1 Announce Type: new Abstract: Neural operators evaluate parametric partial differential equations cheaply but degrade sharply outside their training distribution. Physics-informed ne

LegendBench: A Diagnostic Benchmark for Legend Understanding with Counterfactual Interventions

arXiv:2609.24172v1 Announce Type: new Abstract: Legends are fundamental to chart understanding, as reliable interpretation requires correctly binding legend entries to corresponding visual marks. Whil

Leveraging Inference-Time Compute for Diffusion Models via Global Scheduling of Denoising Trajectories

arXiv:2609.22867v1 Announce Type: new Abstract: Diffusion models generate a sample by traversing a denoising trajectory, a sequence of stochastic noise-reduction steps that transforms pure noise into

LIBERO-VPro: Benchmarking Closed-Loop Visual Robustness of Robotic Foundation Models

arXiv:2609.24350v1 Announce Type: cross Abstract: Robotic foundation models achieve impressive performance on standard manipulation benchmarks, yet these evaluations typically assume clean, timely, an

List Counting Failures Are Not One Phenomenon

arXiv:2609.22230v1 Announce Type: new Abstract: Counting the items in a bracketed list looks trivial, yet open-weight chat models often get it wrong. Prior work usually blames input bottlenecks such a

LLaDA-PRM: A Bidirectional Step-Level Reasoning Evaluator

arXiv:2609.22700v1 Announce Type: new Abstract: Step-level reasoning evaluators are commonly based on autoregressive language models, whose causal attention restricts each step representation to the p

Locally Private Inference for Riemannian Stochastic Optimization

arXiv:2609.22642v1 Announce Type: cross Abstract: We develop inference for manifold-valued population minimizers when each observation belongs to a different participant and only locally private messa

Look Before You Steer: Geometry Predicts SAE Feature Steerability

arXiv:2609.22782v1 Announce Type: new Abstract: Steering with SAE features requires per-feature coefficient tuning, which currently demands intervention sweeps. We ask whether properties of the SAE it

LoRA-generating hypernetworks for efficient on-device LLM generative personalization

arXiv:2609.24979v1 Announce Type: new Abstract: On-device large language models (`LLMs'), e.g. running on mobile phones, are ripe for improvement via personalization. The limited compute resources of

M3GA-Wild: A Large-Scale Dataset and Benchmark for Multi-Modal Multi-session Ground-to-Aerial Place Recognition in Forests

arXiv:2609.23003v1 Announce Type: new Abstract: We present M3GA-Wild, the first benchmark for multi-modal, multi-session ground-to-aerial place recognition in forests. M3GA-Wild unifies and extends ex

Machine-Interpretable Information: Compiling Documents into Searchable and Readable Protocol States

arXiv:2609.23371v1 Announce Type: new Abstract: Long-context language models interface with external knowledge through raw natural language. In retrieval-augmented systems, this creates a persistent i

MCP-GRANITE Benchmark: GRANularity Interface TEsting for MCP-Based LLM Agents

arXiv:2609.24161v1 Announce Type: cross Abstract: As LLM agents increasingly interact with external tools through standardized protocols such as MCP, tool-interface design becomes a critical yet under

Measured Joules, Learned Routes: Learning to Route for Energy-Efficient LLM Serving

arXiv:2609.23085v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are creating rapidly growing inference energy demands as model sizes grow and reasoning trajectori

Measuring the Checker: Mutation Analysis for GPU-Kernel Benchmark Oracles

arXiv:2609.22220v1 Announce Type: new Abstract: Benchmarks for LLM-generated GPU kernels decide correctness with a few random inputs and a loose floating-point tolerance, and their verdicts now feed l

MECAIL: Communication-Aware Incremental Learning for Object Detection with 14.6 KB Spatiotemporal Experts

arXiv:2609.24455v1 Announce Type: new Abstract: Intelligent transportation systems require Incremental Learning (IL) to continually improve their overall performance in dynamic environments. However,

MedGPT-oss: Training a General-Purpose Vision-Language Model for Biomedicine

arXiv:2603.00842v2 Announce Type: replace Abstract: Biomedical multimodal assistants have the potential to unify radiology, pathology, and clinical-text reasoning, yet a critical deployment gap remain

MemCalib: Benchmarking and Optimizing Memory Use in LLM Agents

arXiv:2609.24259v1 Announce Type: new Abstract: The effectiveness of agent memory ultimately depends on whether the underlying LLM gives each memory in context an appropriate degree of influence over

Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization

arXiv:2502.01562v3 Announce Type: replace Abstract: As the general capabilities of artificial intelligence (AI) agents continue to evolve, their ability to learn to master multiple complex tasks throu

Memory That Looks Forward: A Zero-Inference Prospective Term for Personal Memory Retrieval

arXiv:2609.22091v1 Announce Type: new Abstract: Retrieval over a personal memory store is retrospective: it surfaces what resembles the query, and it is blind to what the user has committed to do. We

MIGU: Multimodal Instruction Grounding under Uncertainty for Manipulation Planning

arXiv:2609.24995v1 Announce Type: new Abstract: Understanding natural human instructions is crucial for deploying robots in human-centric environments. We study multimodal instruction grounding, where

MimicAgent: Quadruped Skills via Prompt-to-Trajectory Generation

arXiv:2609.24145v1 Announce Type: new Abstract: We present MimicAgent, a prompt-to-trajectory generation framework for learning dynamic quadruped skills. Although reward shaping is extensively used wh

MinCU: A Fine-Grained Benchmark for Grounded Minimal-Change Understanding in Image Pairs

arXiv:2609.23336v1 Announce Type: new Abstract: Localizing and describing fine-grained differences between near-identical images is a critical yet underexplored capability for multimodal large languag

Mind the Gaps: A Curated Benchmark for Form Field Detection

arXiv:2609.23679v1 Announce Type: new Abstract: Form Field Detection (FFD) is a fundamental component of document understanding systems, enabling applications ranging from large-scale industrial digit

MIRA-PRM: Mission-Informed Reusable Roadmap Planning for Mobile Gas-Sensing Inspection

arXiv:2609.22954v1 Announce Type: new Abstract: Mobile gas-sensing inspection requires a mobile platform to reliably reach ordered sampling poses. We present MIRA-PRM, a mission-informed probabilistic

MIS-Bench: Benchmarking Multimodal LLMs for Psychotherapeutic Interpersonal Skills Assessment

arXiv:2609.22778v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly used as evaluators, yet their reliability in professional assessment tasks that require expert

Misaligned Clinical Risk Classification and Cost Asymmetry in Open-Weight Large Language Models

arXiv:2609.23999v1 Announce Type: new Abstract: How large language models (LLMs) integrate patient risk with clinical cost tradeoffs remains poorly understood. We investigated how four open-weight LLM

MMS-VPR: A Fine-Grained Multimodal Street-Level Visual Place Recognition Dataset and Evaluation Benchmark for Dense Pedestrian Environments

arXiv:2505.12254v3 Announce Type: replace Abstract: Existing visual place recognition (VPR) datasets predominantly rely on vehicle-mounted imagery, offer limited multimodal diversity, and underreprese

MobileCybench: Evaluating Agent Vulnerability Discovery via Executable Probes

arXiv:2609.23980v1 Announce Type: cross Abstract: AI agents now report vulnerabilities faster than maintainers can review them. Reports often depend on security properties specific to the application,

MoE-ACT: Scaling Multi-Task Bimanual Manipulation with Sparse Task-Conditioned Mixture-of-Experts Transformers

arXiv:2603.15265v2 Announce Type: replace Abstract: Developing a unified policy for multi-task robotic manipulation remains challenging due to policy degradation from task interference and negative tr

MolSC: Leveraging Substituent Contributions to Enhance Fine-grained Molecular Understanding in LLMs

arXiv:2609.23073v1 Announce Type: new Abstract: Recent advances in natural language processing have led to molecular Large Language Models (LLMs) with strong performance across diverse chemistry tasks

Monitorable Chart Reasoning Agents via Verifiable Process Rewards

arXiv:2609.24071v1 Announce Type: new Abstract: Chart reasoning agents are increasingly used to extract actionable insights in critical domains, achieving state-of-the-art performance on multiple benc

Monotone-Constrained Diffusion Models for Long-Horizon Production Forecasting

arXiv:2609.22643v1 Announce Type: new Abstract: Forecasting a long horizon from only the first observations of a sequence is ill-posed: many trajectories are consistent with the same short history. We

Moonworks Lunara: Modeling Artistic Intelligence

arXiv:2609.22272v1 Announce Type: new Abstract: We formulate Artistic Intelligence as exploration driven world realization, leaving space for creative possibility while preserving the semantic, artist