Search: “benchmark”

Prompt-Guided Image Editing with Masked Logit Nudging in Visual Autoregressive Models

arXiv:2604.14591v1 Announce Type: new Abstract: We address the problem of prompt-guided image editing in visual autoregressive models. Given a source image and a target text prompt, we aim to modify t

Human

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Model Releases

ProRank: Prompt Warmup via Reinforcement Learning for Small Language Models Reranking

DGX agent

arXiv:2506.03487v3 Announce Type: replace-cross Abstract: Reranking is fundamental to information retrieval and retrieval-augmented generation, with recent Large Language Models (LLMs) significantly a

model-releasesarxiv-cs-cl

17 Apr 2026

Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization

arXiv:2508.10164v2 Announce Type: replace Abstract: Recent advances in Large Reasoning Models (LRMs) have demonstrated strong performance on complex tasks through long Chain-of-Thought (CoT) reasoning

tutorialsarxiv-cs-ai

Purging the Gray Zone: Latent-Geometric Denoising for Precise Knowledge Boundary Awareness

arXiv:2604.14324v1 Announce Type: new Abstract: Large language models (LLMs) often exhibit hallucinations due to their inability to accurately perceive their own knowledge boundaries. Existing abstent

R3D: Revisiting 3D Policy Learning

arXiv:2604.15281v1 Announce Type: new Abstract: 3D policy learning promises superior generalization and cross-embodiment transfer, but progress has been hindered by training instabilities and severe o

Reinforcement Learning via Value Gradient Flow

arXiv:2604.14265v1 Announce Type: new Abstract: We study behavior-regularized reinforcement learning (RL), where regularization toward a reference distribution (the dataset in offline RL or the base m

safetyarxiv-cs-lg

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold

arXiv:2604.13392v1 Announce Type: new Abstract: Tabular data remains prevalent in high-stakes domains such as healthcare and finance, where predictive models are expected to provide both high accuracy

tutorialsarxiv-cs-ai

ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents

arXiv:2604.14261v1 Announce Type: new Abstract: The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-base

SafeHarness: Lifecycle-Integrated Security Architecture for LLM-based Agent Deployment

model-releasesarxiv-cs-ai

arXiv:2604.13630v1 Announce Type: cross Abstract: The performance of large language model (LLM) agents depends critically on the execution harness, the system layer that orchestrates tool use, context

SAGE Celer 2.6 Technical Card

arXiv:2604.14168v1 Announce Type: new Abstract: We introduce SAGE Celer 2.6, the latest in our line of general-purpose Celer models from SAGEA. Celer 2.6 is available in 5B, 10B, and 27B parameter siz

Schema Key Wording as an Instruction Channel in Structured Generation under Constrained Decoding

arXiv:2604.14862v1 Announce Type: new Abstract: Constrained decoding has been widely adopted for structured generation with large language models (LLMs), ensuring that outputs satisfy predefined forma

SelfGrader: Stable Jailbreak Detection for Large Language Models using Token-Level Logits

model-releasesarxiv-cs-ai

arXiv:2604.01473v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are powerful tools for answering user queries, yet they remain highly vulnerable to jailbreak attacks. Existing g

Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation

arXiv:2604.14339v1 Announce Type: new Abstract: Large language models (LLMs) increasingly operate in settings that require reliable long-context understanding, such as retrieval-augmented generation a

SOLIS: Physics-Informed Learning of Interpretable Neural Surrogates for Nonlinear Systems

arXiv:2604.14879v1 Announce Type: new Abstract: Nonlinear system identification must balance physical interpretability with model flexibility. Classical methods yield structured, control-relevant mode

SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning

arXiv:2508.05015v2 Announce Type: replace Abstract: Large language models (LLMs) have shown strong reasoning capabilities when fine-tuned with reinforcement learning (RL). However, such methods requir

researcharxiv-cs-lg

Speak, Segment, Track, Navigate: An Interactive System for Video-Guided Skull-Base Surgery

arXiv:2603.16024v2 Announce Type: replace Abstract: We introduce a speech-guided embodied agent framework for video-guided skull base surgery that dynamically executes perception and image-guidance ta

Stateful Evidence-Driven Retrieval-Augmented Generation with Iterative Reasoning

arXiv:2604.14170v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) grounds Large Language Models (LLMs) in external knowledge but often suffers from flat context representations and

tutorialsarxiv-cs-cl

Applications

Still refuses to write sestinas for some reason, so I don't think all the rough edges are gone.

applicationsethan-mollick--x

Ethan Mollick observes that an AI system (likely Claude or another large language model) still declines to write sestinas, suggesting that certain behavioral constraints or limitations persist despite

StreamCacheVGGT: Streaming Visual Geometry Transformers with Robust Scoring and Hybrid Cache Compression

arXiv:2604.15237v1 Announce Type: new Abstract: Reconstructing dense 3D geometry from continuous video streams requires stable inference under a constant memory budget. Existing O(1) frameworks primar

Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models

arXiv:2604.14629v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown remarkable capabilities in joint vision-language understanding, but their large scale poses significant challen

TennisTV: Do Multimodal Large Language Models Understand Tennis Rallies?

arXiv:2509.15602v5 Announce Type: replace Abstract: Multimodal large language models (MLLMs) excel at general video understanding but struggle with fast, high-frequency sports like tennis, where rally

Think in Latent Thoughts: A New Paradigm for Gloss-Free Sign Language Translation

arXiv:2604.15301v1 Announce Type: new Abstract: Many SLT systems quietly assume that brief chunks of signing map directly to spoken-language words. That assumption breaks down because signers often cr

Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling

arXiv:2601.12145v2 Announce Type: replace Abstract: Softmax attention struggles with long contexts due to structural limitations: the strict sum-to-one constraint forces attention sinks on irrelevant

researcharxiv-cs-lg

TokenFormer: Unify the Multi-Field and Sequential Recommendation Worlds

arXiv:2604.13737v1 Announce Type: cross Abstract: Recommender systems have historically developed along two largely independent paradigms: feature interaction models for modeling correlations among mu

researcharxiv-cs-ai

Topology-Aware Active Learning on Graphs

arXiv:2510.25892v2 Announce Type: replace Abstract: We propose a graph-topological approach to active learning that directly targets the core challenge of exploration versus exploitation under scarce

Uncovering the Fragility of Trustworthy LLMs through Chinese Textual Ambiguity

arXiv:2507.23121v2 Announce Type: replace Abstract: In this work, we study a critical research problem regarding the trustworthiness of large language models (LLMs): how LLMs behave when encountering

UniDoc-RL: Coarse-to-Fine Visual RAG with Hierarchical Actions and Dense Rewards

arXiv:2604.14967v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) extends Large Vision-Language Models (LVLMs) with external visual knowledge. However, existing visual RAG systems t

Unsupervised Skeleton-Based Action Segmentation via Hierarchical Spatiotemporal Vector Quantization

arXiv:2604.15196v1 Announce Type: new Abstract: We propose a novel hierarchical spatiotemporal vector quantization framework for unsupervised skeleton-based temporal action segmentation. We first intr

Local Ai

V-Reflection: Transforming MLLMs from Passive Observers to Active Interrogators

arXiv:2604.03307v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable success, yet they remain prone to perception-related hallucinations in fine-graine

local-aiarxiv-cs-cv

VeriGraphi: A Multi-Agent Framework of Hierarchical RTL Generation for Large Hardware Designs

arXiv:2604.14550v1 Announce Type: cross Abstract: Generating synthesizable Verilog for large, hierarchical hardware designs remains a significant challenge for large language models (LLMs), which stru

VeruSAGE: A Study of Agent-Based Verification for Rust Systems

model-releasesarxiv-cs-ai

arXiv:2512.18436v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown impressive capability to understand and develop code. However, their capability to rigorously reason a

VisPCO: Visual Token Pruning Configuration Optimization via Budget-Aware Pareto-Frontier Learning for Vision-Language Models

arXiv:2604.15188v1 Announce Type: new Abstract: Visual token pruning methods effectively mitigate the quadratic computational growth caused by processing high-resolution images and video frames in vis

WILD-SAM: Phase-Aware Expert Adaptation of SAM for Landslide Detection in Wrapped InSAR Interferograms

arXiv:2604.14540v1 Announce Type: new Abstract: Detecting slow-moving landslides directly from wrapped Interferometric Synthetic Aperture Radar (InSAR) interferograms is crucial for efficient geohazar

Agents

WybeCoder: Verified Imperative Code Generation

arXiv:2603.29088v2 Announce Type: replace-cross Abstract: Recent progress in large language models (LLMs) has substantially advanced automatic code generation and formal theorem proving, yet software

agentsarxiv-cs-ai

xFODE: An Explainable Fuzzy Additive ODE Framework for System Identification

arXiv:2604.14883v1 Announce Type: new Abstract: Recent advances in Deep Learning (DL) have strengthened data-driven System Identification (SysID), with Neural and Fuzzy Ordinary Differential Equation

xFODE+: Explainable Type-2 Fuzzy Additive ODEs for Uncertainty Quantification

arXiv:2604.14880v1 Announce Type: new Abstract: Recent advances in Deep Learning (DL) have boosted data-driven System Identification (SysID), but reliable use requires Uncertainty Quantification (UQ)

A Comparative Study of Dynamic Programming and Reinforcement Learning in Finite Horizon Dynamic Pricing

arXiv:2604.14059v1 Announce Type: cross Abstract: This paper provides a systematic comparison between Fitted Dynamic Programming (DP), where demand is estimated from data, and Reinforcement Learning (

A Lightweight Multi-Metric No-Reference Image Quality Assessment Framework for UAV Imaging

arXiv:2604.13112v1 Announce Type: new Abstract: Reliable image quality assessment is essential in applications where large volumes of images are acquired automatically and must be filtered before furt

A Multimodal Clinically Informed Coarse-to-Fine Framework for Longitudinal CT Registration in Proton Therapy

arXiv:2604.13397v1 Announce Type: new Abstract: Proton therapy offers superior organ-at-risk sparing but is highly sensitive to anatomical changes, making accurate deformable image registration (DIR)

A Proactive EMR Assistant for Doctor-Patient Dialogue: Streaming ASR, Belief Stabilization, and Preliminary Controlled Evaluation

arXiv:2604.13059v1 Announce Type: new Abstract: Most dialogue-based electronic medical record (EMR) systems still behave as passive pipelines: transcribe speech, extract information, and generate the

A Resource-Efficient Hybrid CNN-LSTM network for image-based bean leaf disease classification

arXiv:2604.13835v1 Announce Type: new Abstract: Accurate and resource-efficient automated diagnosis is a cornerstone of modern agricultural expert systems. While Convolutional Neural Networks (CNNs) h

A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model

arXiv:2604.05672v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for open-world robot manipulation, but their practical deployment is often c

researcharxiv-cs-ro

Applications

Abstract 3D Perception for Spatial Intelligence in Vision-Language Models

arXiv:2511.10946v3 Announce Type: replace Abstract: Vision-language models (VLMs) struggle with 3D-related tasks such as spatial cognition and physical understanding, which are crucial for real-world

applicationsarxiv-cs-cv

Adaptive Multi-Scale Channel-Spatial Attention Aggregation Framework for 3D Indoor Semantic Scene Completion Toward Assisting Visually Impaired

arXiv:2602.16385v4 Announce Type: replace Abstract: Independent indoor mobility remains a critical challenge for individuals with visual impairments, largely due to the limited capability of existing

Addressing Overthinking in Large Vision-Language Models via Gated Perception-Reasoning Optimization

arXiv:2601.04442v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) have exhibited strong reasoning capabilities through chain-of-thought mechanisms that generate step-by-st

tutorialsarxiv-cs-cl

Aerial Vision-Language Navigation with a Unified Framework for Spatial, Temporal and Embodied Reasoning

arXiv:2512.08639v3 Announce Type: replace Abstract: Aerial Vision-and-Language Navigation (VLN) aims to enable unmanned aerial vehicles (UAVs) to interpret natural language instructions and navigate c

AeTHERON: Autoregressive Topology-aware Heterogeneous Graph Operator Network for Fluid-Structure Interaction

arXiv:2604.13369v1 Announce Type: cross Abstract: Surrogate modeling of body-driven fluid flows where immersed moving boundaries couple structural dynamics to chaotic, unsteady fluid phenomena remains

Agents

Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning

arXiv:2601.13115v2 Announce Type: replace Abstract: Large Language Models (LLMs) have become a popular interface for human-AI interaction, supporting information seeking and task assistance through na

agentsarxiv-cs-cl