Search: “benchmark”

arXiv:2609.15018v1 Announce Type: new Abstract: We study relative position encoding for multi-view vision Transformers under camera heterogeneity, including varying fields of view (FoVs) or projection

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Research

Generalization Can Emerge in Tabular Foundation Models From a Single Table

DGX agent

arXiv:2511.09665v1 Announce Type: cross Abstract: Deep tabular modelling increasingly relies on in-context learning where, during inference, a model receives a set of (x,y) pairs as context and predic

researcharxiv-cs-ai

15 Sept 2026

GeoTTER: Leveraging Local Geometry of Optimal Transport for Zero-Shot Classification

arXiv:2609.13518v1 Announce Type: new Abstract: We present GeoTTER, a novel framework that redefines optimal transport in the realm of zero-shot classification. Conventional methods often suffer from

safetyarxiv-cs-lg

Gradient-Free Neural Hamilton-Jacobi Reachability for Scalable Safety-Critical Control

model-releasesarxiv-cs-ro

arXiv:2609.14087v1 Announce Type: new Abstract: Hamilton-Jacobi (HJ) reachability provides a principled framework for synthesizing safety certificates and robust controllers for safety-critical roboti

GraMRAG: Orchestrating Multi-Agent Multi-Step Reasoning via Graph Memory with Reinforcement Learning

arXiv:2609.14066v1 Announce Type: cross Abstract: Although existing multi-agent Retrieval-Augmented Generation (RAG) systems have demonstrated promise on complex multimodal reasoning tasks, they remai

Applications

Graph Neural Networks for Influence Maximization in Social Networks: An Unsupervised Minimum Dominating Set Approach

arXiv:2609.13836v1 Announce Type: new Abstract: The Minimum Dominating Set (MDS) problem is a classic NP-hard combinatorial optimization problem with critical applications in social network analysis,

applicationsarxiv-cs-lg

GROOVE: Geometry-Guided Reduction of Operational-Space Jerk in VLA Execution

model-releasesarxiv-cs-ro

arXiv:2609.13695v1 Announce Type: new Abstract: Chunked vision language action (VLA) policies execute several commands per query, but jerk within chunks and across replanning boundaries can induce osc

Grouped Value Attention: Efficient KV Caching via On-Demand Key Reconstruction

arXiv:2609.13285v1 Announce Type: cross Abstract: The KV cache is a primary bottleneck for Transformer decoding: its memory footprint and cache-read traffic grow with sequence length. Grouped-query at

GSLAD: Prototype-Regularized Graph Structure Learning for Multivariate Time Series Anomaly Detection

arXiv:2609.15483v1 Announce Type: new Abstract: Unsupervised multivariate time series anomaly detection methods typically identify anomalies through forecasting, reconstruction, or representation disc

researcharxiv-cs-lg

Hardware

GzDRL: Reproducible and Scalable Deep Reinforcement Learning with Gazebo

arXiv:2609.13243v1 Announce Type: cross Abstract: We present GzDRL, a novel single-process reinforcement learning (RL) framework for Gazebo that overcomes longstanding bottlenecks in scalable, reprodu

hardwarearxiv-cs-lg

Hallucination in Multimodal Foundation Models: A Survey on Causes, Corrections, and Evaluations

arXiv:2410.15359v2 Announce Type: replace Abstract: Multimodal Foundation Models represent a significant leap in artificial intelligence. Among them, Large Vision-Language Models (LVLMs) serve as the

Harmfulness Propagation Dynamics: Layer-wise Trajectories of Adversarial Intent in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.13534v1 Announce Type: new Abstract: We identify extbf{Harmfulness Propagation Dynamics (HPD)}: for harmful prompts, the projection of the last-token hidden state onto a learned harm direct

HarnessBandit: Joint Learnability-Transferability Scheduling for Multi-Harness Agentic Reinforcement Learning

arXiv:2609.13739v1 Announce Type: cross Abstract: Language-model agents are increasingly deployed through diverse harnesses that differ in system prompts, tool schemas, control loops, and trajectory f

Hindsight-Anchored Policy Optimization: Learning Through Hindsight with Thompson Sampling-Inspired Adaptive Gating

arXiv:2603.11321v3 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards improves reasoning in large language models, yet on-policy learning often suffers from cold-sta

How Lossless Is Lossless Speculative Decoding? The Role of Numerical Precision in Orthrus

arXiv:2609.15504v1 Announce Type: cross Abstract: Orthrus is a hybrid autoregressive-diffusion architecture that accelerates autoregressive language-model inference by generating multiple tokens in pa

Hardware

Human Values in a Single Sentence: Moral Presence, Hierarchies, and Transformer Ensembles on the Schwartz Continuum

arXiv:2601.14172v4 Announce Type: replace-cross Abstract: We study neural multi-label classification under severe label imbalance through sentence-level detection of the 19 refined Schwartz human valu

hardwarearxiv-cs-ai

HyperProve: Answer-Guided Hypergraph Expansion for Multi-Hop Question Answering

arXiv:2609.13768v1 Announce Type: new Abstract: Multi-hop question answering often fails when retrieval treats evidence as isolated matches to the original question, since the facts needed to answer a

safetyarxiv-cs-cl

IBBench-Light: A Paired Evaluation of Task-Conditioned Responses to External Directives

arXiv:2609.13725v1 Announce Type: new Abstract: An external record may contain a procedure to apply or text to read, depending on the user's request. IBBench-Light tests both uses against the same rec

Identifying and Transferring Reasoning-Critical Neurons: Improving LLM Inference Reliability via Activation Steering

arXiv:2601.19847v3 Announce Type: replace Abstract: Despite the strong reasoning capabilities of recent large language models (LLMs), achieving reliable performance on challenging tasks often requires

researcharxiv-cs-cl

Interpolation Is Not Invariance: Pair Count Is Not Coverage in Transformation Audits

arXiv:2609.14870v1 Announce Type: cross Abstract: Counting equivalent pairs is a common way to report transformation-audit coverage, but it can substantially overstate the constraints imposed by an au

Inverse Learning of the Altruism and Cost Level in Mixed-Individual Mean Field Games

arXiv:2609.13469v1 Announce Type: cross Abstract: Understanding how humans respond to incentives, both at the individual and collective levels, is crucial to the design of effective policies. Within t

IROH: Insightful Ranking Of Humor using Multi-Stage Hybrid Retrieval with Rationale-Distilled LLM Judges for JOKER 2026 Track Task 1 English

model-releasesarxiv-cs-cl

arXiv:2609.15618v1 Announce Type: cross Abstract: Our team, VANGUARD, presents IROH (Insightful Ranking of Humor), a three-stage retrieval system for JOKER Task 1 English at CLEF 2026, achieving first

ITA-LaCAM: A Complete and Scalable TAPF Solver via Assignment-Aware Configuration-Space Search

model-releasesarxiv-cs-ro

arXiv:2609.14208v1 Announce Type: new Abstract: Combined Target Assignment and Path Finding (TAPF) requires assigning targets for agents while simultaneously planning collision-free paths. We present

JumpStart Your Policy Learning with Lessons from 160,000 Training Runs

arXiv:2609.13730v1 Announce Type: new Abstract: Reliable progress in offline policy learning depends on careful reporting, well-tuned baselines, and evaluation across diverse conditions. Prior work ha

Land Art as a Big-Data Climate Sensor

arXiv:2609.13182v1 Announce Type: cross Abstract: Robert Smithson's 1970 land artwork Spiral Jetty, located in the north arm of Utah's Great Salt Lake, has alternated between submergence and exposure

Learning Continuous Source Responses For Generalizable AI-Generated Image Detection

arXiv:2609.14316v1 Announce Type: new Abstract: Advances in image generation have made synthetic images increasingly difficult to distinguish from real photographs, raising concerns about the trustwor

researcharxiv-cs-cv

Learning Multimodal One-step Flow Policy via Value-weighted Optimal Transport

arXiv:2609.15883v1 Announce Type: cross Abstract: Offline reinforcement learning aims to learn a policy solely from fixed datasets, which often contain multimodal action distributions. Flow policies c

Learning to Solve Hard Problems in RL for LLMs by Never Giving Up

arXiv:2609.13443v1 Announce Type: cross Abstract: We demonstrate that training LLMs with RL does not improve performance equally across a dataset. RL shows large improvements on easy problems that an

Lightning Weave: Improving the Accuracy-Efficiency Frontier of Reasoning Models through Capability Composition

arXiv:2609.14708v1 Announce Type: new Abstract: A core goal of efficient reasoning is to improve the accuracy-efficiency frontier. However, jointly improving reasoning accuracy and inference efficienc

LLMs or Naive Bayes? Old Gems or New Ways

arXiv:2609.13185v1 Announce Type: cross Abstract: Large language models (LLMs) prompt a recurring question in research computing: should classical methods like Naive Bayes (NB) be retired? We benchmar

Long-to-Short Video Evidence Reasoning for Grounded Question Answering

arXiv:2609.15224v1 Announce Type: new Abstract: We present LOVER, a nderline{L}ong to shnderline{O}rt nderline{V}ideo nderline{E}vidence nderline{R}einforced model for grounded question answering (GQA

researcharxiv-cs-cv

Look Before You Leap: Factual Decoding with Internal Attribution Signals

arXiv:2609.15745v1 Announce Type: cross Abstract: Hallucination remains a critical challenge in large language models (LLMs), where early factual errors compound through autoregressive generation in a

Lost-in-the-Middle in Long-Text Generation: Synthetic Dataset, Evaluation Framework, and Mitigation

arXiv:2503.06868v2 Announce Type: replace-cross Abstract: Existing long-text generation methods produce lengthy outputs from short inputs, leaving long-input-to-long-output generation underexplored. A

Machine Learning under Imperfect Data: Challenges and Methods

arXiv:2609.13914v1 Announce Type: new Abstract: Machine-learning models are commonly developed under an assumption that training and test data are sufficiently complete, balanced, labelled, and drawn

Machine Unlearning for Speech Question Answering in Large Audio-Language Models

arXiv:2609.13195v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have recently shown strong capabilities in speech understanding and question answering (QA), but they also inherit

safetyarxiv-cs-cl

MARCUS: An agentic, multimodal vision-language model for cardiac diagnosis and management

arXiv:2603.22179v2 Announce Type: replace Abstract: Cardiovascular disease remains the leading cause of global mortality, with progress hindered by human interpretation of complex cardiac tests. Curre

MarKey: Marginal Utility Guided Greedy Keyframe Selection for Long Video Understanding

arXiv:2609.15408v1 Announce Type: cross Abstract: Long-video understanding remains challenging for multimodal large language models (MLLMs) because densely encoding long frame sequences is computation

researcharxiv-cs-cl

Agents

MedTRACE: Tool-Augmented Multimodal Clinical Reasoning Agents for Evidence-Grounded Decision-Making

arXiv:2609.14823v1 Announce Type: new Abstract: Multimodal clinical decision-making requires reliable reasoning over heterogeneous evidence from electronic health records, medical images, and physiolo

agentsarxiv-cs-cl

Mind2Cloud: EEG-to-Point Cloud Generation with Two-Granularity Diffusion Decoding

arXiv:2609.13991v1 Announce Type: new Abstract: Reconstructing 3D objects from brain signals offers a promising avenue for understanding human visual cognition. While prior work has shown initial succ

ModaLens: Measuring Image Sensitivity in Report-Conditioned Medical VLMs

arXiv:2609.15635v1 Announce Type: cross Abstract: A radiology report can already answer a clinical question, so it is hard to tell whether a vision-language model also uses the image. ModaLens, a pair

ModiGen: A Large Language Model-Based Workflow for Multi-Task Modelica Code Generation

arXiv:2503.18460v2 Announce Type: replace-cross Abstract: Modelica is a widely adopted language for simulating complex physical systems, yet effective model creation and optimization require substanti

MorphoStyle: Motion Style Transfer with Morphology Control

arXiv:2609.14189v1 Announce Type: new Abstract: Human motion may be viewed as a combination of action content, style, and body morphology. Existing motion style transfer methods transfer a reference s

MOSCOPT: Mixture-of-Skills Collective Optimization for LLM Agents

arXiv:2609.14399v1 Announce Type: new Abstract: Natural language prompts and skills serve as the strategic backbone of LLM-based agents. Recent advances in prompt and skill optimization have achieved

Tutorials

Multi-View Molecular Representation Learning with Hierarchical Graphs and Contextualized Fingerprints

arXiv:2609.15611v1 Announce Type: cross Abstract: Molecular property prediction requires representations that generalize from limited labeled data to structurally novel compounds. Existing molecular p

tutorialsarxiv-cs-ai

Multimodal Foundation Models Adaptation based on Domain-Aware Relaxed Orthogonal Subspace for Remote Sensing

arXiv:2609.13654v1 Announce Type: new Abstract: Pretrained foundation models (FMs) have achieved remarkable success in computer vision, yet their high fine-tuning cost limits practical deployment. Par

Natural Language Knowledge Graph Query Execution: Leveraging Controlled Semantics in the LLM Context Window

arXiv:2609.14652v1 Announce Type: cross Abstract: Large Language Model (LLM) applications often transfer domain concepts into the model's context informally, through prompt prose, schema dumps, and ex

Neural-Network Solutions to Real-Space Charge Density and Generalization

arXiv:2609.14906v1 Announce Type: cross Abstract: The Hohenberg-Kohn theorem establishes that, in principle, the ground state (GS) charge density contains all GS information of a many-electron system,

Neuron Activation-based Computation of Logical Explanations for Deep Neural Networks

arXiv:2609.14099v1 Announce Type: cross Abstract: Formal explainability of classifying neural networks (NNs) is an active area of research, providing explanations with provable guarantees of the class

researcharxiv-cs-lg