Search: “models”

Step-level Denoising-time Diffusion Alignment with Multiple Objectives

arXiv:2604.14379v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as a powerful tool for aligning diffusion models with human preferences, typically by optimizing a single rewa

safetyarxiv-cs-cv

17 Apr 2026

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StoryCoder: Narrative Reformulation for Structured Reasoning in LLM Code Generation

DGX agent

arXiv:2604.14631v1 Announce Type: new Abstract: Effective code generation requires both model capability and a problem representation that carefully structures how models reason and plan. Existing app

safetyarxiv-cs-cl

17 Apr 2026

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

17 Apr 2026

A Study of Failure Modes in Two-Stage Human-Object Interaction Detection

arXiv:2604.13448v1 Announce Type: new Abstract: Human-object interaction (HOI) detection aims to detect interactions between humans and objects in images. While recent advances have improved performan

Asymmetric-Loss-Guided Hybrid CNN-BiLSTM-Attention Model for Industrial RUL Prediction with Interpretable Failure Heatmaps

arXiv:2604.13459v1 Announce Type: new Abstract: Turbofan engine degradation under sustained operational stress necessitates robust prognostic systems capable of accurately estimating the Remaining Use

safetyarxiv-cs-lg

Beyond Arrow's Impossibility: Fairness as an Emergent Property of Multi-Agent Collaboration

arXiv:2604.13705v1 Announce Type: new Abstract: Fairness in language models is typically studied as a property of a single, centrally optimized model. As large language models become increasingly agen

safetyarxiv-cs-cl

Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning

arXiv:2604.13891v1 Announce Type: new Abstract: Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need to balance safety and efficiency.

safetyarxiv-cs-ro

Dual-Enhancement Product Bundling: Bridging Interactive Graph and Large Language Model

arXiv:2604.14030v1 Announce Type: new Abstract: Product bundling boosts e-commerce revenue by recommending complementary item combinations. However, existing methods face two critical challenges: (1)

researcharxiv-cs-cl

From Feelings to Metrics: Understanding and Formalizing How Users Vibe-Test LLMs

arXiv:2604.14137v1 Announce Type: new Abstract: Evaluating LLMs is challenging, as benchmark scores often fail to capture models' real-world usefulness. Instead, users often rely on ``vibe-testing'':

Hierarchical DLO Routing with Reinforcement Learning and In-Context Vision-language Models

arXiv:2510.19268v2 Announce Type: replace-cross Abstract: Long-horizon routing tasks of deformable linear objects (DLOs), such as cables and ropes, are common in industrial assembly lines and everyday

agentsarxiv-cs-lg

LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning

arXiv:2604.14140v1 Announce Type: new Abstract: As language models are increasingly deployed for complex autonomous tasks, their ability to reason accurately over longer horizons becomes critical. An

MedRCube: A Multidimensional Framework for Fine-Grained and In-Depth Evaluation of MLLMs in Medical Imaging

arXiv:2604.13756v1 Announce Type: new Abstract: The potential of Multimodal Large Language Models (MLLMs) in domain of medical imaging raise the demands of systematic and rigorous evaluation framework

Multi-Task LLM with LoRA Fine-Tuning for Automated Cancer Staging and Biomarker Extraction

arXiv:2604.13328v1 Announce Type: new Abstract: Pathology reports serve as the definitive record for breast cancer staging, yet their unstructured format impedes large-scale data curation. While Large

Synthesizing Instruction-Tuning Datasets with Contrastive Decoding

arXiv:2604.13538v1 Announce Type: new Abstract: Using responses generated by high-performing large language models (LLMs) for instruction tuning has become a widely adopted approach. However, the exis

Training-Free Semantic Multi-Object Tracking with Vision-Language Models

arXiv:2604.14074v1 Announce Type: new Abstract: Semantic Multi-Object Tracking (SMOT) extends multi-object tracking with semantic outputs such as video summaries, instance-level captions, and interact

researcharxiv-cs-cv

TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Exploration

arXiv:2604.14116v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have empowered AI research agents to perform isolated scientific tasks, automating complex, real-world workflows, s

ViBES: A Conversational Agent with Behaviorally-Intelligent 3D Virtual Body

arXiv:2512.14234v2 Announce Type: replace Abstract: Human communication is inherently multimodal and social: words, prosody, and body language jointly carry intent. Yet most prior systems model human

Beyond Scores: Diagnostic LLM Evaluation via Fine-Grained Abilities

arXiv:2604.12191v1 Announce Type: new Abstract: Current evaluations of large language models aggregate performance across diverse tasks into single scores. This obscures fine-grained ability variation

Causal Diffusion Models for Counterfactual Outcome Distributions in Longitudinal Data

arXiv:2604.12992v1 Announce Type: cross Abstract: Predicting counterfactual outcomes in longitudinal data, where sequential treatment decisions heavily depend on evolving patient states, is critical y

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Local Ai

CREG: Compass Relational Evidence Graph for Characterizing Directional Structure in VLM Spatial-Reasoning Attribution

arXiv:2603.20475v3 Announce Type: replace Abstract: Standard attribution heatmaps show where a vision-language model (VLM) focuses, but they do not reveal whether the recovered evidence is organized b

local-aiarxiv-cs-cv

Does Visual Token Pruning Improve Calibration? An Empirical Study on Confidence in MLLMs

arXiv:2604.12035v1 Announce Type: new Abstract: Visual token pruning is a widely used strategy for efficient inference in multimodal large language models (MLLMs), but existing work mainly evaluates i

researcharxiv-cs-cv

Dual-Modality Anchor-Guided Filtering for Test-time Prompt Tuning

arXiv:2604.12403v1 Announce Type: new Abstract: Test-Time Prompt Tuning (TPT) adapts vision-language models using augmented views, but its effectiveness is hindered by the challenge of determining whi

Efficient Adversarial Training via Criticality-Aware Fine-Tuning

arXiv:2604.12780v1 Announce Type: cross Abstract: Vision Transformer (ViT) models have achieved remarkable performance across various vision tasks, with scalability being a key advantage when applied

Applications

GGD-SLAM: Monocular 3DGS SLAM Powered by Generalizable Motion Model for Dynamic Environments

arXiv:2604.12837v1 Announce Type: new Abstract: Visual SLAM algorithms achieve significant improvements through the exploration of 3D Gaussian Splatting (3DGS) representations, particularly in generat

applicationsarxiv-cs-ro

Applications

Interpretable Relational Inference with LLM-Guided Symbolic Dynamics Modeling

arXiv:2604.12806v1 Announce Type: new Abstract: Inferring latent interaction structures from observed dynamics is a fundamental inverse problem in many-body interacting systems. Most neural approaches

applicationsarxiv-cs-lg

Meet Dynamic Individual Preferences: Resolving Conflicting Human Value with Paired Fine-Tuning

arXiv:2604.12479v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have significantly improved the alignment of models with general human preferences. However, a major cha

safetyarxiv-cs-cl

Mitigating Shortcut Learning via Feature Disentanglement in Medical Imaging: A Benchmark Study

arXiv:2602.18502v2 Announce Type: replace Abstract: Although deep learning models in medical imaging often achieve excellent classification performance, they can rely on shortcut learning, exploiting

Mixed-Integer vs. Continuous Model Predictive Control for Binary Thrusters: A Comparative Study

arXiv:2603.19796v3 Announce Type: replace-cross Abstract: Binary on/off thrusters are commonly used for spacecraft attitude and position control during proximity operations. However, their discrete na

researcharxiv-cs-ro

OVAL: Open-Vocabulary Augmented Memory Model for Lifelong Object Goal Navigation

arXiv:2604.12872v1 Announce Type: new Abstract: Object Goal Navigation (ObjectNav) refers to an agent navigating to an object in an unseen environment, which is an ability often required in the accomp

agentsarxiv-cs-ro

Representation geometry shapes task performance in vision-language modeling for CT enterography

arXiv:2604.13021v1 Announce Type: cross Abstract: Computed tomography (CT) enterography is a primary imaging modality for assessing inflammatory bowel disease (IBD), yet the representational choices t

researcharxiv-cs-ai

Tutorials

SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation

arXiv:2604.12273v1 Announce Type: cross Abstract: Flow matching has emerged as a powerful generative framework, with recent few-step methods achieving remarkable inference acceleration. However, we id

tutorialsarxiv-cs-cv

TCL: Enabling Fast and Efficient Cross-Hardware Tensor Program Optimization via Continual Learning

arXiv:2604.12891v1 Announce Type: new Abstract: Deep learning (DL) compilers rely on cost models and auto-tuning to optimize tensor programs for target hardware. However, existing approaches depend on

TriFit: Trimodal Fusion with Protein Dynamics for Mutation Fitness Prediction

arXiv:2604.12026v1 Announce Type: new Abstract: Predicting the functional impact of single amino acid substitutions (SAVs) is central to understanding genetic disease and engineering therapeutic prote

Local Ai

Uncertainty Guided Exploratory Trajectory Optimization for Sampling-Based Model Predictive Control

arXiv:2604.12149v1 Announce Type: new Abstract: Trajectory optimization depends heavily on initialization. In particular, sampling-based approaches are highly sensitive to initial solutions, and limit

local-aiarxiv-cs-ro

Agentic Driving Coach: Robustness and Determinism of Agentic AI-Powered Human-in-the-Loop Cyber-Physical Systems

arXiv:2604.11705v1 Announce Type: new Abstract: Foundation models, including large language models (LLMs), are increasingly used for human-in-the-loop (HITL) cyber-physical systems (CPS) because found

agentsarxiv-cs-ai

Audio-Omni: Extending Multi-modal Understanding to Versatile Audio Generation and Editing

arXiv:2604.10708v1 Announce Type: cross Abstract: Recent progress in multimodal models has spurred rapid advances in audio understanding, generation, and editing. However, these capabilities are typic

Bridging Linguistic Gaps: Cross-Lingual Mapping in Pre-Training and Dataset for Enhanced Multilingual LLM Performance

arXiv:2604.10590v1 Announce Type: cross Abstract: Multilingual Large Language Models (LLMs) struggle with cross-lingual tasks due to data imbalances between high-resource and low-resource languages, a

safetyarxiv-cs-ai

Bridging the RGB-IR Gap: Consensus and Discrepancy Modeling for Text-Guided Multispectral Detection

arXiv:2604.11234v1 Announce Type: new Abstract: Text-guided multispectral object detection uses text semantics to guide semantic-aware cross-modal interaction between RGB and IR for more robust percep

safetyarxiv-cs-cv

ConfigSpec: Profiling-Based Configuration Selection for Distributed Edge--Cloud Speculative LLM Serving

arXiv:2604.09722v1 Announce Type: cross Abstract: Speculative decoding enables collaborative Large Language Model (LLM) inference across cloud and edge by separating lightweight token drafting from he

safetyarxiv-cs-ai

From UAV Imagery to Agronomic Reasoning: A Multimodal LLM Benchmark for Plant Phenotyping

arXiv:2604.09907v1 Announce Type: cross Abstract: To improve crop genetics, high-throughput, effective and comprehensive phenotyping is a critical prerequisite. While such tasks were traditionally per

Gypscie: A Cross-Platform AI Artifact Management System

arXiv:2604.10311v1 Announce Type: new Abstract: Artificial Intelligence (AI) models, encompassing both traditional machine learning (ML) and more advanced approaches such as deep learning and large la

researcharxiv-cs-ai

LDEPrompt: Layer-importance guided Dual Expandable Prompt Pool for Pre-trained Model-based Class-Incremental Learning

arXiv:2604.11091v1 Announce Type: new Abstract: Prompt-based class-incremental learning methods typically construct a prompt pool consisting of multiple trainable key-prompts and perform instance-leve

researcharxiv-cs-cv

LottieGPT: Tokenizing Vector Animation for Autoregressive Generation

arXiv:2604.11792v1 Announce Type: new Abstract: Despite rapid progress in video generation, existing models are incapable of producing vector animation, a dominant and highly expressive form of multim

MapATM: Enhancing HD Map Construction through Actor Trajectory Modeling

arXiv:2604.11081v1 Announce Type: new Abstract: High-definition (HD) mapping tasks, which perform lane detections and predictions, are extremely challenging due to non-ideal conditions such as view oc

agentsarxiv-cs-cv

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:

RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time

arXiv:2604.11626v1 Announce Type: new Abstract: Most reward models for visual generation reduce rich human judgments to a single unexplained score, discarding the reasoning that underlies preference.

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

Sign Language Recognition in the Age of LLMs

arXiv:2604.11225v1 Announce Type: cross Abstract: Recent Vision Language Models (VLMs) have demonstrated strong performance across a wide range of multimodal reasoning tasks. This raises the question