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RL-Driven Sustainable Land-Use Allocation for the Lake Malawi Basin

arXiv:2604.03768v2 Announce Type: replace Abstract: Unsustainable land-use practices in ecologically sensitive regions threaten biodiversity, water resources, and the livelihoods of millions. This pap

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Human DGX agent

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RL makes MLLMs see better than SFT

DGX agent

arXiv:2510.16333v2 Announce Type: replace Abstract: A dominant assumption in Multimodal Language Model (MLLM) research is that its performance is largely inherited from the LLM backbone, given its imm

model-releasesarxiv-cs-cv

14 Apr 2026

Tutorials

Ro-SLM: Onboard Small Language Models for Robot Task Planning and Operation Code Generation

arXiv:2604.10929v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) provide robots with contextual reasoning abilities to comprehend human instructions. Yet, current LLM-en

tutorialsarxiv-cs-ro

RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation

arXiv:2511.17441v3 Announce Type: replace Abstract: Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due

researcharxiv-cs-ro

RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies

arXiv:2604.09860v1 Announce Type: cross Abstract: The pursuit of general-purpose robotics has yielded impressive foundation models, yet simulation-based benchmarking remains a bottleneck due to rapid

RoboStereo: Dual-Tower 4D Embodied World Models for Unified Policy Optimization

arXiv:2603.12639v2 Announce Type: replace Abstract: Scalable Embodied AI faces fundamental constraints due to prohibitive costs and safety risks of real-world interaction. While Embodied World Models

safetyarxiv-cs-cv

Robust Adversarial Policy Optimization Under Dynamics Uncertainty

model-releasesarxiv-cs-lg

arXiv:2604.10974v1 Announce Type: new Abstract: Reinforcement learning (RL) policies often fail under dynamics that differ from training, a gap not fully addressed by domain randomization or existing

Robust Fair Disease Diagnosis in CT Images

arXiv:2604.09710v1 Announce Type: new Abstract: Automated diagnosis from chest CT has improved considerably with deep learning, but models trained on skewed datasets tend to perform unevenly across pa

Robust Real-Time Coordination of CAVs: A Distributed Optimization Framework under Uncertainty

arXiv:2508.21322v2 Announce Type: replace Abstract: Achieving both safety guarantees and real-time performance in cooperative vehicle coordination remains a fundamental challenge, particularly in dyna

safetyarxiv-cs-ro

RobustMedSAM: Degradation-Resilient Medical Image Segmentation via Robust Foundation Model Adaptation

arXiv:2604.09814v1 Announce Type: new Abstract: Medical image segmentation models built on Segment Anything Model (SAM) achieve strong performance on clean benchmarks, yet their reliability often degr

RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo

arXiv:2505.09368v2 Announce Type: replace Abstract: Standard benchmarks for optical flow, scene flow, and stereo vision algorithms generally focus on model accuracy rather than robustness to image cor

RPA-Check: A Multi-Stage Automated Framework for Evaluating Dynamic LLM-based Role-Playing Agents

arXiv:2604.11655v1 Announce Type: cross Abstract: The rapid adoption of Large Language Models (LLMs) in interactive systems has enabled the creation of dynamic, open-ended Role-Playing Agents (RPAs).

local-aiarxiv-cs-ai

rPPG-VQA: A Video Quality Assessment Framework for Unsupervised rPPG Training

arXiv:2604.11156v1 Announce Type: new Abstract: Unsupervised remote photoplethysmography (rPPG) promises to leverage unlabeled video data, but its potential is hindered by a critical challenge: traini

Agents

RTMC: Step-Level Credit Assignment via Rollout Trees

arXiv:2604.11037v1 Announce Type: cross Abstract: Multi-step agentic reinforcement learning benefits from fine-grained credit assignment, yet existing approaches offer limited options: critic-free met

agentsarxiv-cs-ai

RUMLEM: A Dictionary-Based Lemmatizer for Romansh

arXiv:2604.11233v1 Announce Type: new Abstract: Lemmatization -- the task of mapping an inflected word form to its dictionary form -- is a crucial component of many NLP applications. In this paper, we

researcharxiv-cs-cl

S^3: Structured Sparsity Specification

arXiv:2604.11315v1 Announce Type: cross Abstract: We introduce the Structured Sparsity Specification (S^3), an algebraic framework for defining, composing, and implementing structured sparse patterns.

researcharxiv-cs-ai

S4M: 4-points to Segment Anything

arXiv:2503.05534v3 Announce Type: replace Abstract: Purpose: The Segment Anything Model (SAM) promises to ease the annotation bottleneck in medical segmentation, but overlapping anatomy and blurred bo

Saar-Voice: A Multi-Speaker Saarbrucken Dialect Speech Corpus

arXiv:2604.11803v1 Announce Type: new Abstract: Natural language processing (NLP) and speech technologies have made significant progress in recent years; however, they remain largely focused on standa

local-aiarxiv-cs-cl

Safe Human-to-Humanoid Motion Imitation Using Control Barrier Functions

arXiv:2604.11447v1 Announce Type: new Abstract: Ensuring operational safety is critical for human-to-humanoid motion imitation. This paper presents a vision-based framework that enables a humanoid rob

safetyarxiv-cs-ro

SafeConstellations: Mitigating Over-Refusals in LLMs Through Task-Aware Representation Steering

arXiv:2508.11290v3 Announce Type: replace Abstract: LLMs increasingly exhibit over-refusal behavior, where safety mechanisms cause models to reject benign instructions that seemingly resemble harmful

safetyarxiv-cs-cl

Safety Guarantees in Zero-Shot Reinforcement Learning for Cascade Dynamical Systems

arXiv:2604.10429v1 Announce Type: new Abstract: This paper considers the problem of zero-shot safety guarantees for cascade dynamical systems. These are systems where a subset of the states (the inner

safetyarxiv-cs-ai

Agents

Sanity Checks for Agentic Data Science

arXiv:2604.11003v1 Announce Type: new Abstract: Agentic data science (ADS) pipelines have grown rapidly in both capability and adoption, with systems such as OpenAI Codex now able to directly analyze

agentsarxiv-cs-ai

Sat2Sound: A Unified Framework for Zero-Shot Soundscape Mapping

arXiv:2505.13777v2 Announce Type: replace-cross Abstract: We present Sat2Sound, a unified multimodal framework for geospatial soundscape understanding, designed to predict and map the distribution of

researcharxiv-cs-ai

Hardware

SatReg: Regression-based Neural Architecture Search for Lightweight Satellite Image Segmentation

arXiv:2604.10306v1 Announce Type: new Abstract: As Earth-observation workloads move toward onboard and edge processing, remote-sensing segmentation models must operate under tight latency and energy c

hardwarearxiv-cs-cv

Agents

SBAMP: Sampling Based Adaptive Motion Planning

arXiv:2511.12022v2 Announce Type: replace Abstract: Autonomous robots operating in dynamic environments must balance global path optimality with real-time responsiveness to disturbances. This requires

agentsarxiv-cs-ro

Scalable Stewardship of an LLM-Assisted Clinical Benchmark with Physician Oversight

arXiv:2512.19691v3 Announce Type: replace Abstract: Reference labels for machine-learning benchmarks are increasingly synthesized with LLM assistance, but their reliability remains underexamined. We a

Scaling Up AI-Generated Image Detection with Generator-Aware Prototypes

arXiv:2512.12982v2 Announce Type: replace Abstract: The pursuit of a universal AI-generated image (AIGI) detector often relies on aggregating data from numerous generators to improve generalization. H

Applications

Scene Change Detection with Vision-Language Representation Learning

arXiv:2604.11402v1 Announce Type: new Abstract: Scene change detection (SCD) is crucial for urban monitoring and navigation but remains challenging in real-world environments due to lighting variation

applicationsarxiv-cs-cv

SciPostLayoutTree: A Dataset for Structural Analysis of Scientific Posters

arXiv:2511.18329v3 Announce Type: replace Abstract: Scientific posters play a vital role in academic communication by presenting ideas through visual summaries. Analyzing reading order and parent-chil

SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences?

arXiv:2604.10718v1 Announce Type: new Abstract: Accelerating scientific discovery requires the identification of which experiments would yield the best outcomes before committing resources to costly p

SCITUNE: Aligning Large Language Models with Human-Curated Scientific Multimodal Instructions

arXiv:2307.01139v2 Announce Type: replace-cross Abstract: Instruction finetuning is a popular paradigm to align large language models (LLM) with human intent. Despite its popularity, this idea is less

SCMAPR: Self-Correcting Multi-Agent Prompt Refinement for Complex-Scenario Text-to-Video Generation

arXiv:2604.05489v3 Announce Type: replace Abstract: Text-to-Video (T2V) generation has benefited from recent advances in diffusion models, yet current systems still struggle under complex scenarios, w

Hardware

SCNO: Spiking Compositional Neural Operator -- Towards a Neuromorphic Foundation Model for Nuclear PDE Solving

arXiv:2604.11625v1 Announce Type: cross Abstract: Neural operators have emerged as powerful surrogates for partial differential equation (PDE) solvers, yet they are typically trained as monolithic mod

hardwarearxiv-cs-ai

Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling

arXiv:2512.12675v2 Announce Type: replace-cross Abstract: Subject-driven image generation has advanced from single- to multi-subject composition, while neglecting distinction, the ability to distingui

SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting

arXiv:2604.10688v1 Announce Type: cross Abstract: On-policy reinforcement learning has become the dominant paradigm for reasoning alignment in large language models, yet its sparse, outcome-level rewa

safetyarxiv-cs-ai

ScoRe-Flow: Complete Distributional Control via Score-Based Reinforcement Learning for Flow Matching

arXiv:2604.10962v1 Announce Type: new Abstract: Flow Matching (FM) policies have emerged as an efficient backbone for robotic control, offering fast and expressive action generation that underpins rec

researcharxiv-cs-ro

Applications

Score-matching-based Structure Learning for Temporal Data on Networks

arXiv:2412.07469v3 Announce Type: replace-cross Abstract: Causal discovery is a crucial initial step in establishing causality from empirical data and background knowledge. Numerous algorithms have be

applicationsarxiv-cs-lg

Script-a-Video: Deep Structured Audio-visual Captions via Factorized Streams and Relational Grounding

arXiv:2604.11244v1 Announce Type: new Abstract: Advances in Multimodal Large Language Models (MLLMs) are transforming video captioning from a descriptive endpoint into a semantic interface for both vi

Search-MIND: Training-Free Multi-Modal Medical Image Registration

arXiv:2604.09743v1 Announce Type: cross Abstract: Multi-modal image registration plays a critical role in precision medicine but faces challenges from non-linear intensity relationships and local opti

local-aiarxiv-cs-cv

SEARL: Joint Optimization of Policy and Tool Graph Memory for Self-Evolving Agents

arXiv:2604.07791v2 Announce Type: replace Abstract: Recent advances in Reinforcement Learning with Verifiable Rewards (RLVR) have demonstrated significant potential in single-turn reasoning tasks. Wit

safetyarxiv-cs-ai

SecureVibeBench: Evaluating Secure Coding Capabilities of Code Agents with Realistic Vulnerability Scenarios

arXiv:2509.22097v3 Announce Type: replace-cross Abstract: Large language model-powered code agents are rapidly transforming software engineering, yet the security risks of their generated code have be

See Fair, Speak Truth: Equitable Attention Improves Grounding and Reduces Hallucination in Vision-Language Alignment

arXiv:2604.09749v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) frequently hallucinate objects that are absent from the visual input, often because attention during decoding i

safetyarxiv-cs-cv

Seeing No Evil: Blinding Large Vision-Language Models to Safety Instructions via Adversarial Attention Hijacking

model-releasesarxiv-cs-cl

arXiv:2604.10299v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) rely on attention-based retrieval of safety instructions to maintain alignment during generation. Existing attack

Seeing Through Deception: Uncovering Misleading Creator Intent in Multimodal News with Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2505.15489v4 Announce Type: replace-cross Abstract: The impact of multimodal misinformation arises not only from factual inaccuracies but also from the misleading narratives that creators delibe

Seeing Through the Tool: A Controlled Benchmark for Occlusion Robustness in Foundation Segmentation Models

arXiv:2604.11711v1 Announce Type: new Abstract: Occlusion, where target structures are partially hidden by surgical instruments or overlapping tissues, remains a critical yet underexplored challenge f

Seeing Through Touch: Tactile-Driven Visual Localization of Material Regions

arXiv:2604.11579v1 Announce Type: new Abstract: We address the problem of tactile localization, where the goal is to identify image regions that share the same material properties as a tactile input.

local-aiarxiv-cs-cv

Seg2Change: Adapting Open-Vocabulary Semantic Segmentation Model for Remote Sensing Change Detection

arXiv:2604.11231v1 Announce Type: new Abstract: Change detection is a fundamental task in remote sensing, aiming to quantify the impacts of human activities and ecological dynamics on land-cover chang

Select Smarter, Not More: Prompt-Aware Evaluation Scheduling with Submodular Guarantees

arXiv:2604.11328v1 Announce Type: new Abstract: Automatic prompt optimization (APO) hinges on the quality of its evaluation signal, yet scoring every prompt candidate on the full training set is prohi