Search: “framework”

Learning Evidence Highlighting for Frozen LLMs

arXiv:2604.22565v1 Announce Type: cross Abstract: Large Language Models (LLMs) can reason well, yet often miss decisive evidence when it is buried in long, noisy contexts. We introduce HiLight, an Evi

Learning from Natural Language Feedback for Personalized Question Answering

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DGX agent

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

model-releasesarxiv-cs-ai

27 Apr 2026

LLMPhy: Parameter-Identifiable Physical Reasoning Combining Large Language Models and Physics Engines

arXiv:2411.08027v3 Announce Type: replace-cross Abstract: Most learning-based approaches to complex physical reasoning sidestep the crucial problem of parameter identification (e.g., mass, friction) t

Mixed Membership sub-Gaussian Models

arXiv:2604.22633v1 Announce Type: cross Abstract: The Gaussian mixture model is widely used in unsupervised learning, owing to its simplicity and interpretability. However, a fundamental limitation of

MTT-Bench: Predicting Social Dominance in Mice via Multimodal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2604.22492v1 Announce Type: cross Abstract: Understanding social dominance in animal behavior is critical for neuroscience and behavioral studies. In this work, we explore the capability of Mult

Multimodal Diffusion to Mutually Enhance Polarized Light and Low Resolution EBSD Data

arXiv:2604.22212v1 Announce Type: cross Abstract: In spite of the utility of 3-D electron back-scattered diffraction (EBSD) microscopy, the data collection process can be time-consuming with serial-se

tutorialsarxiv-cs-cv

Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form

arXiv:2408.16286v5 Announce Type: replace Abstract: Designing a safe policy for uncertain environments is crucial in real-world control systems. However, this challenge remains inadequately addressed

safetyarxiv-cs-lg

Nuclear Diffusion Models for Low-Rank Background Suppression in Videos

arXiv:2509.20886v2 Announce Type: replace Abstract: Video sequences often contain structured noise and background artifacts that obscure dynamic content, posing challenges for accurate analysis and re

applicationsarxiv-cs-cv

OmniOVCD: Streamlining Open-Vocabulary Change Detection with SAM 3

arXiv:2601.13895v2 Announce Type: replace-cross Abstract: Change Detection (CD) is a fundamental task in remote sensing. It monitors the evolution of land cover over time. Based on this, Open-Vocabula

On Pareto Optimality for Parametric Choice Bandits

arXiv:2501.19277v4 Announce Type: replace-cross Abstract: We study online assortment optimization under stochastic choice when a decision maker simultaneously values cumulative revenue performance and

One Shot Learning for Edge Detection on Point Clouds

arXiv:2604.22354v1 Announce Type: new Abstract: Each scanner possesses its unique characteristics and exhibits its distinct sampling error distribution. Training a network on a dataset that includes d

tutorialsarxiv-cs-cv

Online Distributional Regression

arXiv:2407.08750v4 Announce Type: replace-cross Abstract: Large-scale streaming data are common in modern machine learning applications and have led to the development of online learning algorithms. M

applicationsarxiv-cs-lg

Optimal Question Selection from a Large Question Bank for Clinical Field Recovery in Conversational Psychiatric Intake

arXiv:2604.22067v1 Announce Type: cross Abstract: Psychiatric intake is a sequential, high-stakes information-gathering process in which clinicians must decide what to ask, in what order, and how to i

PermaFrost-Attack: Stealth Pretraining Seeding(SPS) for planting Logic Landmines During LLM Training

arXiv:2604.22117v1 Announce Type: cross Abstract: Aligned large language models(LLMs) remain vulnerable to adversarial manipulation, and their dependence on web-scale pretraining creates a subtle but

PoseFM: Relative Camera Pose Estimation Through Flow Matching

arXiv:2604.22350v1 Announce Type: new Abstract: Monocular visual odometry (VO) is a fundamental computer vision problem with applications in autonomous navigation, augmented reality and more. While de

agentsarxiv-cs-cv

PreMoE: Proactive Inference for Efficient Mixture-of-Experts

arXiv:2505.17639v3 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models offer dynamic computation, but are typically deployed as static full-capacity models, missing opportunities for depl

PrivSTRUCT: Untangling Data Purpose Compliance of Privacy Policies in Google Play Store

arXiv:2604.22157v1 Announce Type: cross Abstract: Existing research typically treats privacy policies as flat, uniform text, extracting information without regard for the document's logical hierarchy.

tutorialsarxiv-cs-ai

PrivUn: Unveiling Latent Ripple Effects and Shallow Forgetting in Privacy Unlearning

arXiv:2604.22076v1 Announce Type: cross Abstract: Large language models (LLMs) often memorize private information during training, raising serious privacy concerns. While machine unlearning has emerge

researcharxiv-cs-cl

RedVLA: Physical Red Teaming for Vision-Language-Action Models

arXiv:2604.22591v1 Announce Type: new Abstract: The real-world deployment of Vision-Language-Action (VLA) models remains limited by the risk of unpredictable and irreversible physical harm. However, w

safetyarxiv-cs-ro

ReLeVAnT: Relevance Lexical Vectors for Accurate Legal Text Classification

arXiv:2604.22292v1 Announce Type: cross Abstract: The classification of legal documents from an unstructured data corpus has several crucial applications in downstream tasks. Documents relevant to cou

applicationsarxiv-cs-ai

ReLIC-SGG: Relation Lattice Completion for Open-Vocabulary Scene Graph Generation

arXiv:2604.22546v1 Announce Type: new Abstract: Open-vocabulary scene graph generation (SGG) aims to describe visual scenes with flexible relation phrases beyond a fixed predicate set. Existing method

researcharxiv-cs-cv

ResRank: Unifying Retrieval and Listwise Reranking via End-to-End Joint Training with Residual Passage Compression

arXiv:2604.22180v1 Announce Type: cross Abstract: Large language model (LLM) based listwise reranking has emerged as the dominant paradigm for achieving state-of-the-art ranking effectiveness in infor

Rethinking Retrieval-Augmented Generation as a Cooperative Decision-Making Problem

arXiv:2602.18734v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has demonstrated strong effectiveness in knowledge-intensive tasks by grounding language generation in ex

Rethinking XAI Evaluation: A Human-Centered Audit of Shapley Benchmarks in High-Stakes Settings

arXiv:2604.22662v1 Announce Type: cross Abstract: Shapley values are a cornerstone of explainable AI, yet their proliferation into competing formulations has created a fragmented landscape with little

Robust Localization for Autonomous Vehicles in Highway Scenes

arXiv:2604.22040v1 Announce Type: new Abstract: Localization for autonomous vehicles on highways remains under-explored compared to urban roads, and state-of-the-art methods for urban scenes degrade w

agentsarxiv-cs-ro

SAMIDARE: Advanced Tracking-by-Segmentation for Dense Scenarios

arXiv:2604.22162v1 Announce Type: new Abstract: Automated sports analysis demands robust multi-object tracking (MOT), yet segmentation-based methods often struggle with mask errors and ID switches in

researcharxiv-cs-cv

Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning

arXiv:2511.14427v3 Announce Type: replace-cross Abstract: Effective contact-rich manipulation requires robots to synergistically leverage vision, force, and proprioception. However, Reinforcement Lear

safetyarxiv-cs-lg

SOLAR-RL: Semi-Online Long-horizon Assignment Reinforcement Learning

arXiv:2604.22558v1 Announce Type: cross Abstract: As Multimodal Large Language Models (MLLMs) mature, GUI agents are evolving from static interactions to complex navigation. While Reinforcement Learni

agentsarxiv-cs-ai

StateX: Enhancing RNN Recall via Post-training State Expansion

arXiv:2509.22630v3 Announce Type: replace-cross Abstract: Recurrent neural networks (RNNs), such as linear attention and state-space models, have gained popularity due to their constant per-token comp

STEM: Structure-Tracing Evidence Mining for Knowledge Graphs-Driven Retrieval-Augmented Generation

arXiv:2604.22282v1 Announce Type: new Abstract: Knowledge Graph-based Question Answering (KGQA) plays a pivotal role in complex reasoning tasks but remains constrained by two persistent challenges: th

researcharxiv-cs-cl

Sum-of-Checks: Structured Reasoning for Surgical Safety with Large Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2604.22156v1 Announce Type: cross Abstract: Purpose: Accurate assessment of the Critical View of Safety (CVS) during laparoscopic cholecystectomy is essential to prevent bile duct injury, a comp

System-Mediated Attention Imbalances Make Vision-Language Models Say Yes

arXiv:2601.12430v2 Announce Type: replace Abstract: Vision-language model (VLM) hallucination is commonly linked to imbalanced allocation of attention across input modalities: system, image and text.

safetyarxiv-cs-cl

The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check

arXiv:2601.12979v3 Announce Type: replace Abstract: The pursuit of real-time agentic interaction has driven interest in Diffusion-based Large Language Models (dLLMs) as alternatives to auto-regressive

agentsarxiv-cs-cl

The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology

arXiv:2505.20435v3 Announce Type: replace-cross Abstract: Existing interpretability methods for Large Language Models (LLMs) predominantly capture linear directions or isolated features. This overlook

Time-Localized Parametric Decomposition of Respiratory Airflow for Sub-Breath Analysis

model-releasesarxiv-cs-lg

arXiv:2604.22695v1 Announce Type: cross Abstract: Respiratory airflow signals provide critical insight into breathing mechanics, yet conventional analysis methods remain limited in their ability to ch

TTS-PRISM: A Perceptual Reasoning and Interpretable Speech Model for Fine-Grained Diagnosis

arXiv:2604.22225v1 Announce Type: new Abstract: While generative text-to-speech (TTS) models approach human-level quality, monolithic metrics fail to diagnose fine-grained acoustic artifacts or explai

safetyarxiv-cs-cl

UniSonate: A Unified Model for Speech, Music, and Sound Effect Generation with Text Instructions

arXiv:2604.22209v1 Announce Type: cross Abstract: Generative audio modeling has largely been fragmented into specialized tasks, text-to-speech (TTS), text-to-music (TTM), and text-to-audio (TTA), each

UR^2: Unify RAG and Reasoning through Reinforcement Learning

arXiv:2508.06165v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown strong capabilities through two complementary paradigms: Retrieval-Augmented Generation (RAG) for know

Video Analysis and Generation via a Semantic Progress Function

arXiv:2604.22554v1 Announce Type: new Abstract: Transformations produced by image and video generation models often evolve in a highly non-linear manner: long stretches where the content barely change

applicationsarxiv-cs-cv

When LoRA Betrays: Backdooring Text-to-Image Models by Masquerading as Benign Adapters

arXiv:2602.21977v4 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has emerged as a leading technique for efficiently fine-tuning text-to-image diffusion models, and its widespread adoptio

researcharxiv-cs-cv

When Models Outthink Their Safety: Unveiling and Mitigating Self-Jailbreak in Large Reasoning Models

arXiv:2510.21285v4 Announce Type: replace Abstract: Large Reasoning Models (LRMs) achieve strong performance on complex multi-step reasoning, yet they still exhibit severe safety failures such as harm

A Comprehensive Guide to Differential Privacy: From Theory to User Expectations

arXiv:2509.03294v3 Announce Type: replace-cross Abstract: The increasing availability of personal data has enabled significant advances in fields such as machine learning, healthcare, and cybersecurit

tutorialsarxiv-cs-ai

A-IC3: Learning-Guided Adaptive Inductive Generalization for Hardware Model Checking

model-releasesarxiv-cs-lg

arXiv:2604.21688v1 Announce Type: cross Abstract: The IC3 algorithm represents the state-of-the-art (SOTA) hardware model checking technique, owing to its robust performance and scalability. A signifi

A Replicable Robotics Awareness Method Using LLM-Enabled Robotics Interaction: Evidence from a Corporate Challenge

arXiv:2604.21377v1 Announce Type: new Abstract: Large language models are increasingly being explored as interfaces between humans and robotic systems, yet there remains limited evidence on how such t

researcharxiv-cs-ro

Adaptive Instruction Composition for Automated LLM Red-Teaming

arXiv:2604.21159v1 Announce Type: cross Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifyin

tutorialsarxiv-cs-ai

Adaptive Soft Error Protection for Neural Network Processing

arXiv:2407.19664v3 Announce Type: replace Abstract: Previous research on selective protection for neural network components typically exploits only static vulnerability differences. Although these met

Adaptive Test-Time Compute Allocation with Evolving In-Context Demonstrations

arXiv:2604.21018v1 Announce Type: new Abstract: While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from

ADS-POI: Agentic Spatiotemporal State Decomposition for Next Point-of-Interest Recommendation

arXiv:2604.20846v1 Announce Type: cross Abstract: Next point-of-interest (POI) recommendation requires modeling user mobility as a spatiotemporal sequence, where different behavioral factors may evolv