Search: “models”

The Pragmatic Persona: Discovering LLM Persona through Bridging Inference

arXiv:2604.24079v1 Announce Type: cross Abstract: Large Language Models (LLMs) reveal inherent and distinctive personas through dialogue. However, most existing persona discovery approaches rely on su

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Research

Toward Theoretical Insights into Diffusion Trajectory Distillation via Operator Merging

DGX agent

arXiv:2505.16024v2 Announce Type: replace-cross Abstract: Diffusion trajectory distillation accelerates sampling by training a student model to approximate the multi-step denoising trajectories of a p

researcharxiv-cs-ai

28 Apr 2026

UpstreamQA: A Modular Framework for Explicit Reasoning on Video Question Answering Tasks

arXiv:2604.23145v1 Announce Type: cross Abstract: Video Question Answering (VideoQA) demands models that jointly reason over spatial, temporal, and linguistic cues. However, the task's inherent comple

YOLOv8 to YOLO11: A Comprehensive Architecture In-depth Comparative Review

arXiv:2501.13400v3 Announce Type: replace-cross Abstract: In the field of deep learning-based computer vision, YOLO is revolutionary. With respect to deep learning models, YOLO is also the one that is

researcharxiv-cs-ai

Zero-to-CAD: Agentic Synthesis of Interpretable CAD Programs at Million-Scale Without Real Data

arXiv:2604.24479v1 Announce Type: new Abstract: Computer-Aided Design (CAD) models are defined by their construction history: a parametric recipe that encodes design intent. However, existing large-sc

CharTide: Data-Centric Chart-to-Code Generation via Tri-Perspective Tuning and Inquiry-Driven Evolution

arXiv:2604.22192v1 Announce Type: new Abstract: Chart-to-code generation demands strict visual precision and syntactic correctness from Vision-Language Models (VLMs). However, existing approaches are

CNSL-bench: Benchmarking the Sign Language Understanding Capabilities of MLLMs on Chinese National Sign Language

arXiv:2604.22367v1 Announce Type: cross Abstract: Sign language research has achieved significant progress due to the advances in large language models (LLMs). However, the intrinsic ability of LLMs t

Conditional Diffusion Posterior Alignment for Sparse-View CT Reconstruction

arXiv:2604.21960v1 Announce Type: cross Abstract: Computed Tomography (CT) is a widely used imaging modality in medical and industrial applications. To limit radiation exposure and measurement time, t

safetyarxiv-cs-cv

Emergent Strategic Reasoning Risks in AI: A Taxonomy-Driven Evaluation Framework

arXiv:2604.22119v1 Announce Type: new Abstract: As reasoning capacity and deployment scope grow in tandem, large language models (LLMs) gain the capacity to engage in behaviors that serve their own ob

safetyarxiv-cs-ai

GazeVLA: Learning Human Intention for Robotic Manipulation

arXiv:2604.22615v1 Announce Type: new Abstract: Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstra

applicationsarxiv-cs-ro

Knowledge-driven Augmentation and Retrieval for Integrative Temporal Adaptation

arXiv:2604.22098v1 Announce Type: new Abstract: Time introduces fundamental challenges in model development and deployment: models are usually trained on historical data while deployed on future data

applicationsarxiv-cs-cl

Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation

arXiv:2604.22302v1 Announce Type: new Abstract: Recent text-to-image (T2I) models have demonstrated impressive capabilities in photorealistic synthesis and instruction following. However, their reliab

Learning from Natural Language Feedback for Personalized Question Answering

arXiv:2508.10695v2 Announce Type: replace-cross Abstract: Personalization is crucial for enhancing both the effectiveness and user satisfaction of language technologies, particularly in information-se

Recognition Without Authorization: LLMs and the Moral Order of Online Advice

arXiv:2604.22143v1 Announce Type: cross Abstract: Large language models are increasingly used to mediate everyday interpersonal dilemmas, yet how their advisory defaults interact with the concentrated

safetyarxiv-cs-cl

Tensor Network Estimation of Distribution Algorithms

arXiv:2412.19780v2 Announce Type: replace Abstract: Tensor networks are a tool first employed in the context of many-body quantum physics that now have a wide range of uses across the computational sc

researcharxiv-cs-lg

Thermal background reduction for mid-infrared imaging by low-rank background and sparse point-source modelling

arXiv:2604.22351v1 Announce Type: cross Abstract: Mid-infrared astronomy from the ground faces critical challenges in accurately detecting and quantifying sources due to the dominant spatially and tim

safetyarxiv-cs-cv

TreeCoder: Systematic Exploration and Optimisation of Decoding and Constraints for LLM Code Generation

model-releasesarxiv-cs-lg

arXiv:2511.22277v2 Announce Type: replace Abstract: Large language models (LLMs) have shown remarkable ability to generate code, yet their outputs often violate syntactic or semantic constraints when

CAP: Controllable Alignment Prompting for Unlearning in LLMs

arXiv:2604.21251v1 Announce Type: cross Abstract: Large language models (LLMs) trained on unfiltered corpora inherently risk retaining sensitive information, necessitating selective knowledge unlearni

CSC: Turning the Adversary's Poison against Itself

arXiv:2604.21416v1 Announce Type: cross Abstract: Poisoning-based backdoor attacks pose significant threats to deep neural networks by embedding triggers in training data, causing models to misclassif

DMAP: A Distribution Map for Text

arXiv:2602.11871v2 Announce Type: replace Abstract: Large Language Models (LLMs) are a powerful tool for statistical text analysis, with derived sequences of next-token probability distributions offer

researcharxiv-cs-cl

ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming

model-releasesarxiv-cs-lg

arXiv:2505.05261v3 Announce Type: replace-cross Abstract: Two-stage stochastic programming (2SP) offers a basic framework for modelling decision-making under uncertainty, yet scalability remains a cha

Neural surrogates for crystal growth dynamics with variable supersaturation: explicit vs. implicit conditioning

model-releasesarxiv-cs-lg

arXiv:2604.21753v1 Announce Type: cross Abstract: Simulations of crystal growth are performed by using Convolutional Recurrent Neural Network surrogate models, trained on a dataset of time sequences c

Local Ai

Neutron and X-ray Diffraction Reveal the Limits of Long-Range Machine Learning Potentials for Medium-Range Order in Silica Glass

arXiv:2604.21222v1 Announce Type: cross Abstract: Glassy silica is a foundational material in optics and electronics, yet accurately predicting its medium-range order (MRO) remains a major challenge f

local-aiarxiv-cs-lg

Optimal Aggregation of LLM and PRM Signals for Efficient Test-Time Scaling

arXiv:2510.13918v2 Announce Type: replace Abstract: Process reward models (PRMs) are a cornerstone of test-time scaling (TTS), designed to verify and select the best responses from large language mode

researcharxiv-cs-cl

OptiVerse: A Comprehensive Benchmark towards Optimization Problem Solving

model-releasesarxiv-cs-cl

arXiv:2604.21510v1 Announce Type: new Abstract: While Large Language Models (LLMs) demonstrate remarkable reasoning, complex optimization tasks remain challenging, requiring domain knowledge and robus

ReaGeo: Reasoning-Enhanced End-to-End Geocoding with LLMs

arXiv:2604.21357v1 Announce Type: new Abstract: This paper proposes ReaGeo, an end-to-end geocoding framework based on large language models, designed to overcome the limitations of traditional multi-

researcharxiv-cs-ai

Robustness Analysis of POMDP Policies to Observation Perturbations

arXiv:2604.21256v1 Announce Type: new Abstract: Policies for Partially Observable Markov Decision Processes (POMDPs) are often designed using a nominal system model. In practice, this model can deviat

safetyarxiv-cs-ai

Secure LLM Fine-Tuning via Safety-Aware Probing

arXiv:2505.16737v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have achieved remarkable success across many applications, but their ability to generate harmful content raises s

Local Ai

TabSHAP

arXiv:2604.21120v1 Announce Type: cross Abstract: Large Language Models (LLMs) fine-tuned on serialized tabular data are emerging as powerful alternatives to traditional tree-based models, particularl

local-aiarxiv-cs-cl

To See the Unseen: on the Generalization Ability of Transformers in Symbolic Reasoning

arXiv:2604.21632v1 Announce Type: new Abstract: We investigate the ability of decoder-only transformer models to perform abstract symbolic reasoning; specifically solving propositional logic reasoning

Tool Attention Is All You Need: Dynamic Tool Gating and Lazy Schema Loading for Eliminating the MCP/Tools Tax in Scalable Agentic Workflows

arXiv:2604.21816v1 Announce Type: new Abstract: The Model Context Protocol (MCP) has become a common interface for connecting large language model (LLM) agents to external tools, but its reliance on s

WFM: 3D Wavelet Flow Matching for Ultrafast Multi-Modal MRI Synthesis

arXiv:2604.21146v1 Announce Type: new Abstract: Diffusion models have achieved remarkable quality in multi-modal MRI synthesis, but their computational cost (hundreds of sampling steps and separate mo

Who Defines 'Best'? Towards Interactive, User-Defined Evaluation of LLM Leaderboards

arXiv:2604.21769v1 Announce Type: new Abstract: LLM leaderboards are widely used to compare models and guide deployment decisions. However, leaderboard rankings are shaped by evaluation priorities set

Adapting TrOCR for Printed Tigrinya Text Recognition: Word-Aware Loss Weighting for Cross-Script Transfer Learning

arXiv:2604.20813v1 Announce Type: new Abstract: Transformer-based OCR models have shown strong performance on Latin and CJK scripts, but their application to African syllabic writing systems remains l

AVISE: Framework for Evaluating the Security of AI Systems

arXiv:2604.20833v1 Announce Type: cross Abstract: As artificial intelligence (AI) systems are increasingly deployed across critical domains, their security vulnerabilities pose growing risks of high-p

Can 'AI' Be a Doctor? A Study of Empathy, Readability, and Alignment in Clinical LLMs

arXiv:2604.20791v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in healthcare, yet their communicative alignment with clinical standards remains insufficiently

Can We Locate and Prevent Stereotypes in LLMs?

arXiv:2604.19764v1 Announce Type: cross Abstract: Stereotypes in large language models (LLMs) can perpetuate harmful societal biases. Despite the widespread use of models, little is known about where

CHASM: Unveiling Covert Advertisements on Chinese Social Media

arXiv:2604.20511v1 Announce Type: cross Abstract: Current benchmarks for evaluating large language models (LLMs) in social media moderation completely overlook a serious threat: covert advertisements,

applicationsarxiv-cs-ai

COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling

arXiv:2604.20720v1 Announce Type: cross Abstract: Large language models (LLMs) often exhibit performance disparities across languages, with naive multilingual fine-tuning frequently degrading performa

Context Attribution with Multi-Armed Bandit Optimization

arXiv:2506.19977v2 Announce Type: replace Abstract: Understanding which parts of the retrieved context contribute to a large language model's generated answer is essential for building interpretable a

researcharxiv-cs-ai

Cooperative Profiles Predict Multi-Agent LLM Team Performance in AI for Science Workflows

model-releasesarxiv-cs-cl

arXiv:2604.20658v1 Announce Type: new Abstract: Multi-agent systems built from teams of large language models (LLMs) are increasingly deployed for collaborative scientific reasoning and problem-solvin

DialToM: A Theory of Mind Benchmark for Forecasting State-Driven Dialogue Trajectories

arXiv:2604.20443v1 Announce Type: cross Abstract: Large Language Models (LLMs) have been shown to possess Theory of Mind (ToM) abilities. However, it remains unclear whether this stems from robust rea

Agents

EvolveSignal: A Large Language Model Powered Coding Agent for Discovering Traffic Signal Control Strategies

arXiv:2509.03335v3 Announce Type: replace Abstract: In traffic engineering, fixed-time traffic signal control remains widely used for its low cost, stability, and interpretability. However, its design

agentsarxiv-cs-lg

Agents

From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents

arXiv:2604.19775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of reasoning, planning, and acting within interactive environments.

agentsarxiv-cs-ai

From Scene to Object: Text-Guided Dual-Gaze Prediction

arXiv:2604.20191v1 Announce Type: cross Abstract: Interpretable driver attention prediction is crucial for human-like autonomous driving. However, existing datasets provide only scene-level global gaz

GRPO-VPS: Enhancing Group Relative Policy Optimization with Verifiable Process Supervision for Effective Reasoning

arXiv:2604.20659v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has advanced the reasoning capabilities of Large Language Models (LLMs) by leveraging direct out

safetyarxiv-cs-ai

Tutorials

Image Generators are Generalist Vision Learners

arXiv:2604.20329v1 Announce Type: cross Abstract: Recent works show that image and video generators exhibit zero-shot visual understanding behaviors, in a way reminiscent of how LLMs develop emergent

tutorialsarxiv-cs-ai

Improving Large-Scale Recommender Systems with Auxiliary Learning

arXiv:2510.02215v3 Announce Type: replace Abstract: Training large-scale recommendation models under a single global objective implicitly assumes homogeneity across user populations. However, real-wor

applicationsarxiv-cs-lg