Search: “models”

PL-MTEB: Polish Massive Text Embedding Benchmark

arXiv:2405.10138v2 Announce Type: replace Abstract: In this paper, we introduce the Polish Massive Text Embedding Benchmark (PL-MTEB), a comprehensive benchmark for text embeddings in the Polish langu

PreMoE: Proactive Inference for Efficient Mixture-of-Experts

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DGX agent

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

researcharxiv-cs-lg

27 Apr 2026

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

Region Matters: Efficient and Reliable Region-Aware Visual Place Recognition

arXiv:2604.22390v1 Announce Type: new Abstract: Visual Place Recognition (VPR) determines a query image's geographic location by matching it against geotagged databases. However, existing methods stru

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 Math Reasoning Evaluation: A Robust LLM-as-a-Judge Framework Beyond Symbolic Rigidity

arXiv:2604.22597v1 Announce Type: new Abstract: Recent advancements in large language models have led to significant improvements across various tasks, including mathematical reasoning, which is used

Applications

Segment Any-Quality Images with Generative Latent Space Enhancement

arXiv:2503.12507v3 Announce Type: replace Abstract: Despite their success, Segment Anything Models (SAMs) experience significant performance drops on severely degraded, low-quality images, limiting th

applicationsarxiv-cs-cv

SSG: Logit-Balanced Vocabulary Partitioning for LLM Watermarking

arXiv:2604.22438v1 Announce Type: cross Abstract: Watermarking has emerged as a promising technique for tracing the authorship of content generated by large language models (LLMs). Among existing appr

Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem

arXiv:2506.17299v2 Announce Type: replace-cross Abstract: As large language models (LLMs) become increasingly deployed in safety-critical applications, the lack of systematic methods to assess their v

Tracing the complexity profiles of different linguistic phenomena through the intrinsic dimension of LLM representations

arXiv:2601.03779v2 Announce Type: replace Abstract: We explore intrinsic dimension (ID) of LLM representations as a marker of linguistic complexity. Specifically, we test whether ID differences across

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

A-THENA: Early Intrusion Detection for IoT with Time-Aware Hybrid Encoding and Network-Specific Augmentation

model-releasesarxiv-cs-lg

arXiv:2604.21623v1 Announce Type: cross Abstract: The proliferation of Internet of Things (IoT) devices has significantly expanded attack surfaces, making IoT ecosystems particularly susceptible to so

Absorber LLM: Harnessing Causal Synchronization for Test-Time Training

arXiv:2604.20915v1 Announce Type: cross Abstract: Transformers suffer from a high computational cost that grows with sequence length for self-attention, making inference in long streams prohibited by

AgentDoG: A Diagnostic Guardrail Framework for AI Agent Safety and Security

arXiv:2601.18491v2 Announce Type: replace Abstract: The rise of AI agents introduces complex safety and security challenges arising from autonomous tool use and environmental interactions. Current gua

Beyond Pixels: Introspective and Interactive Grounding for Visualization Agents

arXiv:2604.21134v1 Announce Type: new Abstract: Vision-Language Models (VLMs) frequently misread values, hallucinate details, and confuse overlapping elements in charts. Current approaches rely solely

BioMiner: A Multi-modal System for Automated Mining of Protein-Ligand Bioactivity Data from Literature

arXiv:2604.21508v1 Announce Type: new Abstract: Protein-ligand bioactivity data published in the literature are essential for drug discovery, yet manual curation struggles to keep pace with rapidly gr

BiTDiff: Fine-Grained 3D Conducting Motion Generation via BiMamba-Transformer Diffusion

arXiv:2604.04395v2 Announce Type: replace Abstract: 3D conducting motion generation aims to synthesize fine-grained conductor motions from music, with broad potential in music education, virtual perfo

safetyarxiv-cs-cv

CI-Work: Benchmarking Contextual Integrity in Enterprise LLM Agents

arXiv:2604.21308v1 Announce Type: cross Abstract: Enterprise LLM agents can dramatically improve workplace productivity, but their core capability, retrieving and using internal context to act on a us

climt-paraformer: Stable Emulation of Convective Parameterization using a Temporal Memory-aware Transformer

arXiv:2604.21085v1 Announce Type: cross Abstract: Accurate representation of moist convective sub-grid-scale processes remains a major challenge in global climate models, as traditional parameterizati

researcharxiv-cs-lg

CorridorVLA: Explicit Spatial Constraints for Generative Action Heads via Sparse Anchors

arXiv:2604.21241v1 Announce Type: cross Abstract: Vision--Language--Action (VLA) models often use intermediate representations to connect multimodal inputs with continuous control, yet spatial guidanc

Data-Driven Open-Loop Simulation for Digital-Twin Operator Decision Support in Wastewater Treatment

arXiv:2604.20935v1 Announce Type: cross Abstract: Wastewater treatment plants (WWTPs) need digital-twin-style decision support tools that can simulate plant response under prescribed control plans, to

Dialect vs Demographics: Quantifying LLM Bias from Implicit Linguistic Signals vs. Explicit User Profiles

arXiv:2604.21152v1 Announce Type: cross Abstract: As state-of-the-art Large Language Models (LLMs) have become ubiquitous, ensuring equitable performance across diverse demographics is critical. Howev

Do MLLMs Understand Pointing? Benchmarking and Enhancing Referential Reasoning in Egocentric Vision

arXiv:2604.21461v1 Announce Type: new Abstract: Egocentric AI agents, such as smart glasses, rely on pointing gestures to resolve referential ambiguities in natural language commands. However, despite

FairyFuse: Multiplication-Free LLM Inference on CPUs via Fused Ternary Kernels

model-releasesarxiv-cs-lg

arXiv:2604.20913v1 Announce Type: new Abstract: Large language models are increasingly deployed on CPU-only platforms where memory bandwidth is the primary bottleneck for autoregressive generation. We

Fine-Tuning Regimes Define Distinct Continual Learning Problems

model-releasesarxiv-cs-lg

arXiv:2604.21927v1 Announce Type: new Abstract: Continual learning (CL) studies how models acquire tasks sequentially while retaining previously learned knowledge. Despite substantial progress in benc

Flipping Against All Odds: Reducing LLM Coin Flip Bias via Verbalized Rejection Sampling

arXiv:2506.09998v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can often accurately describe probability distributions using natural language, yet they still struggle to genera

safetyarxiv-cs-cl

Generative Discovery of Magnetic Insulators under Competing Physical Constraints

arXiv:2604.21073v1 Announce Type: cross Abstract: Discovering materials that must simultaneously satisfy multiple competing constraints remains a central challenge in computational materials design, p

GerAV: Towards New Heights in German Authorship Verification using Fine-Tuned LLMs on a New Benchmark

arXiv:2601.13711v2 Announce Type: replace Abstract: Authorship verification (AV) is the task of determining whether two texts were written by the same author and has been studied extensively, predomin

GiVA: Gradient-Informed Bases for Vector-Based Adaptation

arXiv:2604.21901v1 Announce Type: cross Abstract: As model sizes continue to grow, parameter-efficient fine-tuning has emerged as a powerful alternative to full fine-tuning. While LoRA is widely adopt

HARBOR: Automated Harness Optimization

arXiv:2604.20938v1 Announce Type: cross Abstract: Long-horizon language-model agents are dominated, in lines of code and in operational complexity, not by their underlying model but by the harness tha

Tutorials

Information Bottleneck-Guided Heterogeneous Graph Learning for Interpretable Neurodevelopmental Disorder Diagnosis

arXiv:2502.20769v3 Announce Type: replace Abstract: Developing interpretable models for neurodevelopmental disorders (NDDs) diagnosis presents significant challenges in effectively encoding, decoding,

tutorialsarxiv-cs-cv

Interpretable facial dynamics as behavioral and perceptual traces of deepfakes

arXiv:2604.21760v1 Announce Type: new Abstract: Deepfake detection research has largely converged on deep learning approaches that, despite strong benchmark performance, offer limited insight into wha

Job Skill Extraction via LLM-Centric Multi-Module Framework

arXiv:2604.21525v1 Announce Type: new Abstract: Span-level skill extraction from job advertisements underpins candidate-job matching and labor-market analytics, yet generative large language models (L

Applications

LAF-Based Evaluation and UTTL-Based Learning Strategies with MIATTs

arXiv:2604.20944v1 Announce Type: cross Abstract: In many real-world machine learning (ML) applications, the true target cannot be precisely defined due to ambiguity or subjectivity information. To ad

applicationsarxiv-cs-ai

LatRef-Diff: Latent and Reference-Guided Diffusion for Facial Attribute Editing and Style Manipulation

arXiv:2604.21279v1 Announce Type: new Abstract: Facial attribute editing and style manipulation are crucial for applications like virtual avatars and photo editing. However, achieving precise control

researcharxiv-cs-cv

Listen and Chant Before You Read: The Ladder of Beauty in LM Pre-Training

arXiv:2604.21265v1 Announce Type: new Abstract: We show that pre-training a Transformer on music before language significantly accelerates language acquisition. Using piano performances (MAESTRO datas

Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression

arXiv:2505.13527v3 Announce Type: replace-cross Abstract: Despite substantial advancements in aligning large language models (LLMs) with human values, current safety mechanisms remain susceptible to j

Losing our Tail, Again: (Un)Natural Selection & Multilingual LLMs

arXiv:2507.03933v3 Announce Type: replace Abstract: Multilingual Large Language Models considerably changed how technologies influence language. While previous technologies could mediate or assist hum

MaskDiME: Adaptive Masked Diffusion for Precise and Efficient Visual Counterfactual Explanations

arXiv:2602.18792v3 Announce Type: replace Abstract: Visual counterfactual explanations aim to reveal the minimal semantic modifications that can alter a model's prediction, providing causal and interp

Mind the Prompt: Self-adaptive Generation of Task Plan Explanations via LLMs

arXiv:2604.21092v1 Announce Type: new Abstract: Integrating Large Language Models (LLMs) into complex software systems enables the generation of human-understandable explanations of opaque AI processe

Tutorials

Mixture of Sequence: Theme-Aware Mixture-of-Experts for Long-Sequence Recommendation

arXiv:2604.20858v1 Announce Type: cross Abstract: Sequential recommendation has rapidly advanced in click-through rate prediction due to its ability to model dynamic user interests. A key challenge, h

tutorialsarxiv-cs-ai

Omission Constraints Decay While Commission Constraints Persist in Long-Context LLM Agents

arXiv:2604.20911v1 Announce Type: cross Abstract: LLM agents deployed in production operate under operator-defined behavioral policies (system-prompt instructions such as prohibitions on credential di

OmniFit: Multi-modal 3D Body Fitting via Scale-agnostic Dense Landmark Prediction

arXiv:2604.21575v1 Announce Type: new Abstract: Fitting an underlying body model to 3D clothed human assets has been extensively studied, yet most approaches focus on either single-modal inputs such a

Applications

Optimizing Diffusion Priors with a Single Observation

arXiv:2604.21066v1 Announce Type: new Abstract: While diffusion priors generate high-quality posterior samples across many inverse problems, they are often trained on limited training sets or purely s

applicationsarxiv-cs-cv

PAT3D: Physics-Augmented Text-to-3D Scene Generation

arXiv:2511.21978v2 Announce Type: replace Abstract: We introduce PAT3D, the first physics-augmented text-to-3D scene generation framework that integrates vision-language models with physics-based simu

researcharxiv-cs-cv

Pre-trained LLMs Meet Sequential Recommenders: Efficient User-Centric Knowledge Distillation

arXiv:2604.21536v1 Announce Type: cross Abstract: Sequential recommender systems have achieved significant success in modeling temporal user behavior but remain limited in capturing rich user semantic

Preferences of a Voice-First Nation: Large-Scale Pairwise Evaluation and Preference Analysis for TTS in Indian Languages

arXiv:2604.21481v1 Announce Type: new Abstract: Crowdsourced pairwise evaluation has emerged as a scalable approach for assessing foundation models. However, applying it to Text to Speech(TTS) introdu

Propensity Inference: Environmental Contributors to LLM Behaviour

arXiv:2604.21098v1 Announce Type: new Abstract: Motivated by loss of control risks from misaligned AI systems, we develop and apply methods for measuring language models' propensity for unsanctioned b