Search: “benchmark”

PackLab: A Comprehensive Framework for Developing, Training, and Evaluating MLLMs in Robotic Bin Packing

arXiv:2609.23784v1 Announce Type: new Abstract: Robotic bin packing requires long-horizon sequential decision-making, as each object placement affects the available space for subsequent packing. Exist

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PAOLI: Pose-free Articulated Object Learning from Sparse-view Images

DGX agent

arXiv:2509.04276v3 Announce Type: replace Abstract: We present a method for modeling articulated objects from sparse images with unknown camera poses. Existing approaches require dense multi-view obse

applicationsarxiv-cs-cv

22 Sept 2026

ParA-LLM: A Unified Approach to Paralinguistic and Acoustic Speech Understanding

arXiv:2609.22771v1 Announce Type: cross Abstract: Recent advances in Audio LLMs have achieved human-level speech recognition, yet existing systems struggle to capture paralinguistic aspects such as sp

Per-Query Gating of LLM Rerankers for Multi-Hop Retrieval

arXiv:2609.22880v1 Announce Type: cross Abstract: LLM rerankers add of the order of $0.2-0.3 per 1,000 queries and about a second of tail latency on top of a graph-augmented dense pipeline such as Hip

researcharxiv-cs-cl

PETR: Prompt Ensembling with Training-free Routing for Vision-Language Models

arXiv:2609.23600v1 Announce Type: new Abstract: Prompt learning efficiently adapts vision-language models (VLMs) to downstream tasks, but gains on seen classes often come at the expense of generalizat

Phrase-Level Robotic Guqin Performance: Bimanual Motion Planning and Audio-Tactile Interaction Monitoring

arXiv:2609.24133v1 Announce Type: new Abstract: Recent advances in humanoid robotics and embodied intelligence have enabled robots to perform increasingly complex manipulation tasks. However, musical

Physics-Informed Classical and Quantum Neural Networks for One-Dimensional Schrodinger Eigenvalue Problems

arXiv:2609.22189v1 Announce Type: cross Abstract: The Schrodinger equation in one spatial dimension admits a small set of exactly solvable potentials that serve as natural proving grounds for any new

researcharxiv-cs-lg

PhysReflect: Geometry and Perception Guided Diffusion for Physically-Plausible Mirror Reflections

arXiv:2609.23442v1 Announce Type: new Abstract: Diffusion models generate high-quality images, yet often violate the physical laws governing mirror reflections. Reflections often suffer from geometric

safetyarxiv-cs-cv

PINGU: Extending Air-Bearing Spacecraft Emulators with Open-Source Actuators and Learned Control for Contact-Rich Proximity Operations

arXiv:2609.23554v1 Announce Type: new Abstract: Low-cost planar air-bearing testbeds have matured into a standard proxy for free-flying spacecraft GNC, but they remain largely thruster-only and are ra

Planning and Rendering in Concert: DeepFusion of Autoregressive Layouts and Diffusion for Visual Text Generation

arXiv:2609.22916v1 Announce Type: new Abstract: Generating text-rich images from prompts requires both textual fidelity and the coherent integration of text into the surrounding image. An explicit lay

Local Ai

PosEviLoc: Position-Conditioned Spatial Evidence for Language-Based 3D Localization

arXiv:2609.23534v1 Announce Type: new Abstract: Language-based 3D localization retrieves the point-cloud submap containing a target position from descriptions of nearby objects and their spatial relat

local-aiarxiv-cs-cv

Positive Pair Geometry Matters: Optimal Transport for Contrastive Learning of Visual Representations

arXiv:2609.24125v1 Announce Type: new Abstract: Contrastive self-supervised learning has achieved strong performance by learning representations from multiple augmented views of the same image. Howeve

Predicting Out-of-Distribution Generalization of Neural Operators via Observable Spectral Error Decomposition

arXiv:2609.23529v1 Announce Type: new Abstract: Neural operators have emerged as powerful surrogates for solving partial differential equations (PDEs), yet their reliability under distribution shift r

researcharxiv-cs-lg

Hardware

PREM: Prefix-Steered Recurrent Memory for Long-Video Understanding

arXiv:2609.23601v1 Announce Type: new Abstract: Long-video understanding must capture transient visual evidence under strict token budgets, yet existing methods compress frames, append memory tokens,

hardwarearxiv-cs-cv

Prior-Amortized In-Context Bayesian Inference for Generalized Linear Mixed-Effects Models

arXiv:2609.24422v1 Announce Type: new Abstract: Hierarchical data is ubiquitous in the empirical sciences and is most commonly analyzed with generalized linear mixed-effects models (GLMMs). Bayesian i

PrismGPT: Proxy-Guided Learning for Region-Aware Photo Editing with Self-Synthesized Reasoning

arXiv:2609.24768v1 Announce Type: new Abstract: Professional photo finishing relies on both global adjustments and region-specific local edits guided by semantic masks, yet current automated methods h

Privacy Personalization Trade offs in LLMs: The Impact of Stylometric Signal Reduction on User-Specific Text Generation

arXiv:2609.22112v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated the ability to generate user-specific text with high stylistic fidelity. However, the personal data that

Propose, Verify, Commit: Evidence-Grounded Memory for Long-Horizon Multi-Actor Conversations

arXiv:2609.23465v1 Announce Type: new Abstract: Long-horizon conversational memory is especially challenging in multi-actor settings, where relevant evidence is distributed across participants and con

PRQuant: Permutation Residual Quantization for Low-Overhead Inference

arXiv:2609.22106v1 Announce Type: cross Abstract: Accuracy of Low-bit quantization of linear layers is often dominated by a small number of outliers. Although existing methods, such as smoothing, rota

researcharxiv-cs-cv

RADAR: Retrieval-Augmented Detector with Adversarial Refinement for Adaptive LLM-Generated Fake News Detection

arXiv:2601.03981v3 Announce Type: replace Abstract: To efficiently combat the spread of LLM-generated misinformation in the news domain, we present RADAR, a Retrieval-Augmented Detector with Adversari

Applications

RAILS: Retrieval-Augmented Incremental LLM Clustering at Scale

arXiv:2609.24464v1 Announce Type: new Abstract: Using a Large Language Model (LLM) as the clusterer at production scale is hard: prompts cannot hold the entire label space, and per-document serial pro

applicationsarxiv-cs-lg

Local Ai

Rebekah 1.8b now available

🚀 THE EDGE AI FAMILY HAS ARRIVED. Today we’re opening the doors to a new generation of open-source and open-weight edge AI models from Next GenAi. Meet Rebekah AI 1.8B. 🧠⚡ Small enough to run at the e

local-air-ollama

Applications

Re:CAP - Auditing Retrieval Coverage in Production RAG Pipelines

arXiv:2609.24122v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is hard to monitor in production: exhaustive relevance labels do not exist for non-stationary multi-million-passage

applicationsarxiv-cs-cl

Recognition, Simulation, and Refusal: A Contamination-Aware Study of Classic Psychological Effects in LLM Agents

arXiv:2609.22090v1 Announce Type: new Abstract: An LLM producing the response pattern associated with a human psychological effect is not the same claim as the LLM possessing that bias. We present Psy

Reflective Policy Optimization

arXiv:2406.03678v2 Announce Type: replace Abstract: On-policy reinforcement learning methods, like Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO), often demand extensiv

safetyarxiv-cs-lg

Hardware

RegVGGT: Sustainable Visual Geometry Grounding for Streaming via Regulated Memory

arXiv:2609.23286v1 Announce Type: new Abstract: 3D reconstruction from a lengthy video stream input poses a dilemma for feed-forward reconstruction models (FFRMs), that a whole-stream inference contex

hardwarearxiv-cs-cv

Reinforcement learning with an expectile-based objective

arXiv:2602.09300v2 Announce Type: replace Abstract: We consider the policy evaluation and control in a finite horizon reinforcement learning (RL) setting under an expectile-based objective. First, we

safetyarxiv-cs-lg

Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents

arXiv:2601.15322v3 Announce Type: replace-cross Abstract: Tool-using agents can repeat a final decision while changing their recorded execution. We introduce the Determinism-Faithfulness Assurance Har

Residual Primitive Fitting of 3D Shapes with SuperFrusta

arXiv:2512.09201v2 Announce Type: replace-cross Abstract: We introduce a framework for converting 3D shapes into compact and editable assemblies of analytic primitives, directly addressing the persist

researcharxiv-cs-cv

Resist, Update, Reject: Preference Optimization Installs a Prior-Dependent Reliability Switch

arXiv:2609.22359v1 Announce Type: new Abstract: An aligned model asked to hold its answer against a manipulative source must still update on a reliable one and reject an unreliable one: resistance, re

Revisiting Multi-View Stereo: A Sequence-to-Sequence Formulation

arXiv:2609.24850v1 Announce Type: new Abstract: Computing accurate geometry from multi-view images is a fundamental problem in computer vision. Recent feed-forward (FF) models jointly estimate 3D geom

researcharxiv-cs-cv

RewardVerse: Rubric-Guided Policy Optimization for Video Reward Modeling

arXiv:2609.22947v1 Announce Type: new Abstract: Reinforcement learning (RL) is vital for optimizing video generation models, with a robust reward model (RM) serving as the cornerstone. However, existi

RheOFormer: A generative transformer model for simulation of complex fluids and flows

arXiv:2510.01365v2 Announce Type: replace Abstract: The ability to model mechanics of soft materials under flowing conditions is key in designing and engineering processes and materials with targeted

RiverVLN: Phase-Grounded Temporal Vision--Language Navigation for Unmanned Surface Vehicles

arXiv:2609.23423v1 Announce Type: new Abstract: Vision-language navigation (VLN) has largely been developed for indoor and terrestrial robots, where language can often be treated as a static goal and

Role-Aware Morgan Fingerprints for Reaction Yield Prediction

arXiv:2609.22167v1 Announce Type: new Abstract: Predicting reaction yield from molecular structure and reaction context can cut experimental trial-and-error and speed up condition screening in synthet

researcharxiv-cs-lg

RPMem: Learning Long-Term Recurrent Parametric Memory Across Sessions for LLM Agents

arXiv:2609.23466v1 Announce Type: new Abstract: Long-running LLM agents require memory that persists and evolves across sessions. Text-based memory retrieves and reconstructs past interactions at ever

researcharxiv-cs-cl

SAFe: Segment-guided Aggregation of Feature Densities for Anomaly-aware Segmentation

arXiv:2609.24204v1 Announce Type: new Abstract: Visual segmentation systems encounter objects outside their training distribution during real-world deployment, hindering reliable autonomous systems th

SafeTune: A Unified Faithful Library for Auditing and Repairing Safety Drift in Fine-Tuned LLMs

arXiv:2609.22153v1 Announce Type: new Abstract: Methods for addressing safety drift in fine-tuned Large Language Models (LLMs) are scattered across incompatible implementations, lifecycle stages, and

safetyarxiv-cs-lg

Local Ai

SAGE: Optimal-Stopping Peer Selection for Decentralised Federated Learning

arXiv:2609.23773v1 Announce Type: cross Abstract: Decentralised federated learning replaces server aggregation with peer-to-peer model exchange, making collaborator selection a local decision under un

local-aiarxiv-cs-lg

SalQ-VLM: Fine-Grained Saliency-Guided Quantization for Vision-Language Models

arXiv:2508.03351v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across diverse language tasks, motivating their extension to vision-lan

SCoR: A Hierarchical Framework for Forecasting Relations Between Scientific Concepts

arXiv:2609.22174v1 Announce Type: new Abstract: Anticipating emerging research directions is a critical goal of AI-assisted science. Existing methods mainly predict which concepts will co-occur in fut

Semi-automated reconstruction of indoor geometry from 360-degree video for CFD-based airflow analysis in classrooms

arXiv:2609.23425v1 Announce Type: new Abstract: Computational Fluid Dynamics (CFD) is widely used to evaluate ventilation and contaminant transport in occupied buildings, but deployment at scale is li

SG-FSM: A Self-Guiding Zero-Shot Prompting Paradigm for Multi-Hop Question Answering Based on Finite State Machine

arXiv:2410.17021v2 Announce Type: replace Abstract: Large Language Models with chain-of-thought prompting, such as OpenAI-o1, have shown impressive capabilities in natural language inference tasks. Ho

researcharxiv-cs-cl

ShearFuse-UNet: Hadamard, DCT, and Shearlet Transform Fusion for Next-Day Wildfire Spread Prediction

arXiv:2606.14071v2 Announce Type: replace Abstract: We propose ShearFuse-UNet, a lightweight and computationally efficient deep learning model for next-day wildfire spread prediction from multi-modal

Signal-Informed Temporal Routing for Vinyl Defect Regime Detection

arXiv:2609.23164v1 Announce Type: cross Abstract: Vinyl restoration systems must distinguish isolated clicks, short bursts, dense crackle, and overlapping damage before selecting a repair operation. W

Sim2Real Diffusion: Leveraging Foundation Vision Language Models for Adaptive Automated Driving

arXiv:2507.00236v4 Announce Type: replace Abstract: Simulation-based design, optimization, and validation of autonomous vehicles have proven to be crucial for their improvement over the years. Neverth

Applications

Single Point, Full Mask: Velocity-Guided Level Set Evolution for End-to-End Amodal Segmentation

arXiv:2508.01661v2 Announce Type: replace Abstract: Amodal segmentation aims to recover complete object shapes, including occluded regions, serving as an essential technique for user-centric multimedi

applicationsarxiv-cs-cv

SmoLSTM: A Compact Vision-Language-Action Model with Recurrent Memory that Persists

arXiv:2609.22854v1 Announce Type: cross Abstract: Vision-language-action models often predict actions from only the current observation, which can leave tasks involving object occlusion or visually id