Search: “benchmark”

Measuring the Authority Stack of AI Systems: Empirical Analysis of 366,120 Forced-Choice Responses Across 8 AI Models

arXiv:2604.11216v1 Announce Type: new Abstract: What values, evidence preferences, and source trust hierarchies do AI systems actually exhibit when facing structured dilemmas? We present the first lar

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Measuring What Matters!! Assessing Therapeutic Principles in Mental-Health Conversation

DGX agent

arXiv:2604.05795v2 Announce Type: replace Abstract: The increasing use of large language models in mental health applications calls for principled evaluation frameworks that assess alignment with psyc

model-releasesarxiv-cs-cl

14 Apr 2026

MedLVR: Latent Visual Reasoning for Reliable Medical Visual Question Answering

arXiv:2604.09757v1 Announce Type: cross Abstract: Medical vision--language models (VLMs) have shown strong potential for medical visual question answering (VQA), yet their reasoning remains largely te

MedVeriSeg: Teaching MLLM-Based Medical Segmentation Models to Verify Query Validity Without Extra Training

arXiv:2604.10242v1 Announce Type: new Abstract: Despite recent advances in MLLM-based medical image segmentation, existing LISA-like methods cannot reliably reject false queries and often produce hall

Agents

Mem^2Evolve: Towards Self-Evolving Agents via Co-Evolutionary Capability Expansion and Experience Distillation

arXiv:2604.10923v1 Announce Type: cross Abstract: While large language model--powered agents can self-evolve by accumulating experience or by dynamically creating new assets (i.e., tools or expert age

agentsarxiv-cs-ai

MEMENTO: Teaching LLMs to Manage Their Own Context

arXiv:2604.09852v1 Announce Type: new Abstract: Reasoning models think in long, unstructured streams with no mechanism for compressing or organizing their own intermediate state. We introduce MEMENTO:

METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues

arXiv:2604.11427v1 Announce Type: cross Abstract: Developing non-collaborative dialogue agents traditionally requires the manual, unscalable codification of expert strategies. We propose ours, a metho

Min-k Sampling: Decoupling Truncation from Temperature Scaling via Relative Logit Dynamics

arXiv:2604.11012v1 Announce Type: new Abstract: The quality of text generated by large language models depends critically on the decoding sampling strategy. While mainstream methods such as Top-k, Top

Mirai: Autoregressive Visual Generation Needs Foresight

arXiv:2601.14671v2 Announce Type: replace Abstract: Autoregressive (AR) visual generators model images as sequences of discrete tokens and are trained with a next-token likelihood objective. This stri

MLLM-as-a-Judge Exhibits Model Preference Bias

arXiv:2604.11589v1 Announce Type: new Abstract: Automatic evaluation using multimodal large language models (MLLMs), commonly referred to as MLLM-as-a-Judge, has been widely used to measure model perf

Applications

Modular Delta Merging with Orthogonal Constraints: A Scalable Framework for Continual and Reversible Model Composition

arXiv:2507.20997v4 Announce Type: replace-cross Abstract: In real-world machine learning deployments, models must be continually updated, composed, and when required, selectively undone. However, exis

applicationsarxiv-cs-ai

MoEITS: A Green AI approach for simplifying MoE-LLMs

arXiv:2604.10603v1 Announce Type: cross Abstract: Large language models are transforming all areas of academia and industry, attracting the attention of researchers, professionals, and the general pub

MOSAIC: Multi-Domain Orthogonal Session Adaptive Intent Capture for Prescient Recommendations

arXiv:2604.10147v1 Announce Type: cross Abstract: Capturing user intent across heterogeneous behavioral domains stands as a fundamental challenge in session-based recommender systems. Yet, existing mu

MPAC: A Multi-Principal Agent Coordination Protocol for Interoperable Multi-Agent Collaboration

arXiv:2604.09744v1 Announce Type: cross Abstract: The AI agent ecosystem has converged on two protocols: the Model Context Protocol (MCP) for tool invocation and Agent-to-Agent (A2A) for single-princi

Agents

MSA: Memory Sparse Attention for Efficient End-to-End Memory Model Scaling to 100M Tokens

arXiv:2603.23516v2 Announce Type: replace-cross Abstract: Long-term memory is a cornerstone of human intelligence. Enabling AI to process lifetime-scale information remains a long-standing pursuit in

agentsarxiv-cs-ai

Local Ai

MSTN: A Lightweight and Fast Model for General TimeSeries Analysis

arXiv:2511.20577v3 Announce Type: replace Abstract: Real-world time series often exhibit strong non-stationarity, complex nonlinear dynamics, and behavior expressed across multiple temporal scales, fr

local-aiarxiv-cs-lg

Multi-Granularity Reasoning for Image Quality Assessment via Attribute-Aware Reinforcement Learning to Rank

arXiv:2604.09704v1 Announce Type: new Abstract: Recent advances in reasoning-induced image quality assessment (IQA) have demonstrated the power of reinforcement learning to rank (RL2R) for training vi

safetyarxiv-cs-cv

Multi-Head Attention based interaction-aware architecture for Bangla Handwritten Character Recognition: Introducing a Primary Dataset

arXiv:2604.09717v1 Announce Type: new Abstract: Character recognition is the fundamental part of an optical character recognition (OCR) system. Word recognition, sentence transcription, document digit

Multi-modal, multi-scale representation learning for satellite imagery analysis just needs a good ALiBi

arXiv:2604.10347v1 Announce Type: new Abstract: Vision foundation models have been shown to be effective at processing satellite imagery into representations fit for downstream tasks, however, creatin

Multi-ORFT: Stable Online Reinforcement Fine-Tuning for Multi-Agent Diffusion Planning in Cooperative Driving

arXiv:2604.11734v1 Announce Type: cross Abstract: Closed-loop cooperative driving requires planners that generate realistic multimodal multi-agent trajectories while improving safety and traffic effic

Multinex: Lightweight Low-light Image Enhancement via Multi-prior Retinex

arXiv:2604.10359v1 Announce Type: cross Abstract: Low-light image enhancement (LLIE) aims to restore natural visibility, color fidelity, and structural detail under severe illumination degradation. St

Mycelium-Index: A Streaming Approximate Nearest Neighbor Index with Myelial Edge Decay, Traffic-Driven Reinforcement, and Adaptive Living Hierarchy

model-releasesarxiv-cs-lg

arXiv:2604.11274v1 Announce Type: new Abstract: We present mycelium-index, a streaming approximate nearest neighbor (ANN) index for high-dimensional vector spaces, inspired by the adaptive growth patt

Nano-EmoX: Unifying Multimodal Emotional Intelligence from Perception to Empathy

arXiv:2603.02123v3 Announce Type: replace Abstract: The development of affective multimodal language models (MLMs) has long been constrained by a gap between low-level perception and high-level intera

Neural Stochastic Processes for Satellite Precipitation Refinement

arXiv:2604.10414v1 Announce Type: new Abstract: Accurate precipitation estimation is critical for flood forecasting, water resource management, and disaster preparedness. Satellite products provide gl

Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning

arXiv:2504.13818v4 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as the leading approach for enhancing reasoning capabilities in large langua

NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: AI Flash Portrait (Track 3)

arXiv:2604.11230v1 Announce Type: new Abstract: In this paper, we present a comprehensive overview of the NTIRE 2026 3rd Restore Any Image Model (RAIM) challenge, with a specific focus on Track 3: AI

NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results

arXiv:2604.10634v1 Announce Type: new Abstract: This paper presents an overview of the NTIRE 2026 Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images. Building upon the success

Observe Less, Understand More: Cost-aware Cross-scale Observation for Remote Sensing Understanding

arXiv:2604.11415v1 Announce Type: new Abstract: Remote sensing understanding inherently requires multi-resolution observation, since different targets and application tasks demand different levels of

Omnimodal Dataset Distillation via High-order Proxy Alignment

model-releasesarxiv-cs-cl

arXiv:2604.10666v1 Announce Type: cross Abstract: Dataset distillation compresses large-scale datasets into compact synthetic sets while preserving training performance, but existing methods are large

OmniScript: Towards Audio-Visual Script Generation for Long-Form Cinematic Video

arXiv:2604.11102v1 Announce Type: new Abstract: Current multimodal large language models (MLLMs) have demonstrated remarkable capabilities in short-form video understanding, yet translating long-form

OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation

arXiv:2604.11804v1 Announce Type: new Abstract: In this work, we study Human-Object Interaction Video Generation (HOIVG), which aims to synthesize high-quality human-object interaction videos conditio

Applications

One Scale at a Time: Scale-Autoregressive Modeling for Fluid Flow Distributions

arXiv:2604.11403v1 Announce Type: cross Abstract: Analyzing unsteady fluid flows often requires access to the full distribution of possible temporal states, yet conventional PDE solvers are computatio

applicationsarxiv-cs-ai

Online Covariance Matrix Estimation in Sketched Newton Methods

model-releasesarxiv-cs-lg

arXiv:2502.07114v2 Announce Type: replace-cross Abstract: Given the ubiquity of streaming data, online algorithms have been widely used for parameter estimation, with second-order methods particularly

Online Reasoning Video Object Segmentation

arXiv:2604.11411v1 Announce Type: new Abstract: Reasoning video object segmentation predicts pixel-level masks in videos from natural-language queries that may involve implicit and temporally grounded

Optimal Kinodynamic Motion Planning Through Anytime Bidirectional Heuristic Search with Tight Termination Condition

arXiv:2604.11587v1 Announce Type: new Abstract: This paper introduces Bidirectional Tight Informed Trees (BTIT*), an asymptotically optimal kinodynamic sampling-based motion planning algorithm that in

researcharxiv-cs-ro

Agents

Our technical report, including how we designed the reward and the performance/latency Pareto frontier, is live here: https://cognition.ai/b…

Cognition AI has published a technical report detailing the design methodology behind their reward system, likely related to their Devin AI software engineering agent. The report covers the performanc

agentscognition-ai--x

Hardware

PA-SFM: Tracker-free differentiable acoustic radiation for freehand 3D photoacoustic imaging

arXiv:2604.09643v1 Announce Type: new Abstract: Three-dimensional (3D) handheld photoacoustic tomography typically relies on bulky and expensive external positioning sensors to correct motion artifact

hardwarearxiv-cs-cv

PACO: Proxy-Task Alignment and Online Calibration for On-the-Fly Category Discovery

arXiv:2604.11484v1 Announce Type: new Abstract: On-the-Fly Category Discovery (OCD) requires a model, trained on an offline support set, to recognize known classes while discovering new ones from an o

safetyarxiv-cs-cv

Pando: Do Interpretability Methods Work When Models Won't Explain Themselves?

arXiv:2604.11061v1 Announce Type: cross Abstract: Mechanistic interpretability is often motivated for alignment auditing, where a model's verbal explanations can be absent, incomplete, or misleading.

Para-B&B: Load-Balanced Deterministic Parallelization of Solving MIP

arXiv:2604.09556v1 Announce Type: cross Abstract: Mixed-integer programming (MIP) extends linear programming by incorporating both continuous and integer decision variables, making it widely used in p

Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow

arXiv:2601.15593v2 Announce Type: replace-cross Abstract: Masked Diffusion Language Models (MDLMs) promise parallel token generation and arbitrary-order decoding, yet it remains unclear to what extent

Particle Diffusion Matching: Random Walk Correspondence Search for the Alignment of Standard and Ultra-Widefield Fundus Images

arXiv:2604.10085v1 Announce Type: new Abstract: We propose a robust alignment technique for Standard Fundus Images (SFIs) and Ultra-Widefield Fundus Images (UWFIs), which are challenging to align due

safetyarxiv-cs-cv

PAS: Estimating the target accuracy before domain adaptation

arXiv:2604.09863v1 Announce Type: cross Abstract: The goal of domain adaptation is to make predictions for unlabeled samples from a target domain with the help of labeled samples from a different but

PEMANT: Persona-Enriched Multi-Agent Negotiation for Travel

arXiv:2604.10475v1 Announce Type: new Abstract: Modeling household-level trip generation is fundamental to accurate demand forecasting, traffic flow estimation, and urban system planning. Existing stu

PhyMix: Towards Physically Consistent Single-Image 3D Indoor Scene Generation with Implicit--Explicit Optimization

arXiv:2604.10125v1 Announce Type: new Abstract: Existing single-image 3D indoor scene generators often produce results that look visually plausible but fail to obey real-world physics, limiting their

Point2Pose: Occlusion-Recovering 6D Pose Tracking and 3D Reconstruction for Multiple Unknown Objects Via 2D Point Trackers

arXiv:2604.10415v1 Announce Type: new Abstract: We present Point2Pose, a model-free method for causal 6D pose tracking of multiple rigid objects from monocular RGB-D video. Initialized only from spars

Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage

arXiv:2603.23966v3 Announce Type: replace-cross Abstract: With frequently evolving Advanced Persistent Threats (APTs) in cyberspace, traditional security solutions approaches have become inadequate fo

Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards

arXiv:2509.21882v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is a practical, scalable way to improve large language models on math, code, and other s