Search: “llm”

Stylistic-STORM (ST-STORM) : Perceiving the Semantic Nature of Appearance

arXiv:2604.16086v1 Announce Type: cross Abstract: One of the dominant paradigms in self-supervised learning (SSL), illustrated by MoCo or DINO, aims to produce robust representations by capturing feat

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Subliminal Transfer of Unsafe Behaviors in AI Agent Distillation

DGX agent

arXiv:2604.15559v1 Announce Type: new Abstract: Recent work on subliminal learning demonstrates that language models can transmit semantic traits through data that is semantically unrelated to those t

safetyarxiv-cs-ai

20 Apr 2026

TabularMath: Understanding Math Reasoning over Tables with Large Language Models

model-releasesarxiv-cs-ai

arXiv:2505.19563v4 Announce Type: replace Abstract: Mathematical reasoning has long been a key benchmark for evaluating large language models. Although substantial progress has been made on math word

Target-Oriented Pretraining Data Selection via Neuron-Activated Graph

arXiv:2604.15706v1 Announce Type: new Abstract: Everyday tasks come with a target, and pretraining models around this target is what turns them into experts. In this paper, we study target-oriented la

researcharxiv-cs-cl

Teaching Language Models Mechanistic Explainability Through MechSMILES

arXiv:2512.05722v2 Announce Type: replace Abstract: Chemical reaction mechanisms are the foundation of how chemists evaluate reactivity and feasibility, yet current Computer-Assisted Synthesis Plannin

researcharxiv-cs-lg

Temporal Contrastive Decoding: A Training-Free Method for Large Audio-Language Models

arXiv:2604.15383v1 Announce Type: cross Abstract: Large audio-language models (LALMs) generalize across speech, sound, and music, but unified decoders can exhibit a temporal smoothing bias: transient

The Price of Paranoia: Robust Risk-Sensitive Cooperation in Non-Stationary Multi-Agent Reinforcement Learning

arXiv:2604.15695v1 Announce Type: cross Abstract: Cooperative equilibria are fragile. When agents learn alongside each other rather than in a fixed environment, the process of learning destabilizes th

Transfer Learning from Foundational Optimization Embeddings to Unsupervised SAT Representations

arXiv:2604.15448v1 Announce Type: cross Abstract: Foundational optimization embeddings have recently emerged as powerful pre-trained representations for mixed-integer programming (MIP) problems. These

researcharxiv-cs-ai

Where does output diversity collapse in post-training?

arXiv:2604.16027v1 Announce Type: cross Abstract: Post-trained language models produce less varied outputs than their base counterparts. This output diversity collapse undermines inference-time scalin

researcharxiv-cs-ai

Local Ai

AIPC: Agent-Based Automation for AI Model Deployment with Qualcomm AI Runtime

arXiv:2604.14661v1 Announce Type: cross Abstract: Edge AI model deployment is a multi-stage engineering process involving model conversion, operator compatibility handling, quantization calibration, r

local-aiarxiv-cs-lg

An Intelligent Robotic and Bio-Digestor Framework for Smart Waste Management

arXiv:2604.14882v1 Announce Type: cross Abstract: Rapid urbanization and continuous population growth have made municipal solid waste management increasingly challenging. These challenges highlight th

agentsarxiv-cs-lg

An unsupervised decision-support framework for multivariate biomarker analysis in athlete monitoring

arXiv:2604.14534v1 Announce Type: new Abstract: Purpose. Athlete monitoring is constrained by small cohorts, heterogeneous biomarker scales, limited feasibility of repeated sampling, and the lack of r

APEX-MEM: Agentic Semi-Structured Memory with Temporal Reasoning for Long-Term Conversational AI

arXiv:2604.14362v1 Announce Type: new Abstract: Large language models still struggle with reliable long-term conversational memory: simply enlarging context windows or applying naive retrieval often i

agentsarxiv-cs-cl

Beyond Importance Sampling: Rejection-Gated Policy Optimization

arXiv:2604.14895v1 Announce Type: new Abstract: We propose a new perspective on policy optimization: rather than reweighting all samples by their importance ratios, an optimizer should select which sa

BoundRL: Efficient Structured Text Segmentation through Reinforced Boundary Generation

arXiv:2510.20151v2 Announce Type: replace Abstract: Structured texts refer to texts containing structured elements beyond plain texts, such as code snippets and placeholders. Such structured texts inc

safetyarxiv-cs-cl

CaptionQA: Is Your Caption as Useful as the Image Itself?

model-releasesarxiv-cs-cv

arXiv:2511.21025v2 Announce Type: replace Abstract: Image captions serve as efficient surrogates for visual content in multimodal systems such as retrieval, recommendation, and multi-step agentic infe

CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification

arXiv:2604.14602v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate toxic content, posing significant risks for safe deployment. Current mitigation strategies often degrad

Compressed-Sensing-Guided, Inference-Aware Structured Reduction for Large Language Models

arXiv:2604.14156v1 Announce Type: new Abstract: Large language models deliver strong generative performance but at the cost of massive parameter counts, memory use, and decoding latency. Prior work ha

Continual Learning for fMRI-Based Brain Disorder Diagnosis via Functional Connectivity Matrices Generative Replay

arXiv:2604.14259v1 Announce Type: cross Abstract: Functional magnetic resonance imaging (fMRI) is widely used for studying and diagnosing brain disorders, with functional connectivity (FC) matrices pr

applicationsarxiv-cs-lg

Cornfigurator: Automated Planning for Any-to-Any Multimodal Model Serving

arXiv:2512.14098v3 Announce Type: replace Abstract: Any-to-Any models are an emerging class of multimodal models that accept combinations of text and multimodal data as input and generate them as outp

researcharxiv-cs-lg

Hardware

cuRoboV2: Dynamics-Aware Motion Generation with Depth-Fused Distance Fields for High-DoF Robots

arXiv:2603.05493v2 Announce Type: replace Abstract: Effective robot autonomy requires motion generation that is safe, feasible, and reactive. Current methods are fragmented: fast planners output physi

hardwarearxiv-cs-ro

De-Anonymization at Scale via Tournament-Style Attribution

arXiv:2601.12407v2 Announce Type: replace-cross Abstract: As LLMs rapidly advance and enter real-world use, their privacy implications are increasingly important. We study an authorship de-anonymizati

DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation

arXiv:2602.22839v2 Announce Type: replace Abstract: Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing pre

Differentiable Object Pose Connectivity Metrics for Regrasp Sequence Optimization

arXiv:2604.14733v1 Announce Type: new Abstract: Regrasp planning is often required when one pick-and-place cannot transfer an object from an initial pose to a goal pose while maintaining grasp feasibi

tutorialsarxiv-cs-ro

Domain Fine-Tuning FinBERT on Finnish Histopathological Reports: Train-Time Signals and Downstream Correlations

arXiv:2604.14815v1 Announce Type: new Abstract: In NLP classification tasks where little labeled data exists, domain fine-tuning of transformer models on unlabeled data is an established approach. In

DPSQL+: A Differentially Private SQL Library with a Minimum Frequency Rule

model-releasesarxiv-cs-lg

arXiv:2602.22699v2 Announce Type: replace-cross Abstract: SQL is the de facto interface for exploratory data analysis; however, releasing exact query results can expose sensitive information through m

Local Ai

EEGDM: Learning EEG Representation with Latent Diffusion Model

arXiv:2508.20705v3 Announce Type: replace Abstract: Recent advances in self-supervised learning for EEG representation have largely relied on masked reconstruction, where models are trained to recover

local-aiarxiv-cs-lg

Empowerment Gain and Causal Model Construction: Children and adults are sensitive to controllability and variability in their causal interventions

arXiv:2512.08230v2 Announce Type: replace Abstract: Learning about the causal structure of the world is a fundamental problem for human cognition. Causal models and especially causal learning have pro

Fabricator or dynamic translator?

arXiv:2604.15165v1 Announce Type: new Abstract: LLMs are proving to be adept at machine translation although due to their generative nature they may at times overgenerate in various ways. These overge

researcharxiv-cs-cl

Formalizing the Safety, Security, and Functional Properties of Agentic AI Systems

arXiv:2510.14133v2 Announce Type: replace Abstract: Agentic AI systems, which leverage multiple autonomous agents and large language models (LLMs), are increasingly used to address complex, multi-step

FRAGATA: Semantic Retrieval of HPC Support Tickets via Hybrid RAG over 20 Years of Request Tracker History

arXiv:2604.13721v1 Announce Type: cross Abstract: The technical support team of a supercomputing centre accumulates, over the course of decades, a large volume of resolved incidents that constitute cr

tutorialsarxiv-cs-ai

From Black Box to Glass Box: Cross-Model ASR Disagreement to Prioto Review in Ambient AI Scribe Documentation

arXiv:2604.14152v1 Announce Type: cross Abstract: Ambient AI 'scribe' systems promise to reduce clinical documentation burden, but automatic speech recognition (ASR) errors can remain unnoticed withou

GFT: From Imitation to Reward Fine-Tuning with Unbiased Group Advantages and Dynamic Coefficient Rectification

arXiv:2604.14258v1 Announce Type: cross Abstract: Large language models are typically post-trained using supervised fine-tuning (SFT) and reinforcement learning (RL), yet effectively unifying efficien

Hierarchical Retrieval Augmented Generation for Adversarial Technique Annotation in Cyber Threat Intelligence Text

arXiv:2604.14166v1 Announce Type: new Abstract: Mapping Cyber Threat Intelligence (CTI) text to MITRE ATT&CK technique IDs is a critical task for understanding adversary behaviors and automating threa

safetyarxiv-cs-cl

Hijacking online reviews: sparse manipulation and behavioral buffering in popularity-biased rating systems

arXiv:2604.13049v1 Announce Type: cross Abstract: Online reviews and recommendation systems help users navigate overwhelming choice, but they are vulnerable to self-reinforcing distortions. This paper

Inclusive Kitchen Design for Older Adults: Generative AI Visualizations to Support Mild Cognitive Impairment

arXiv:2604.13203v1 Announce Type: cross Abstract: Mild Cognitive Impairment (MCI) affects 15-20% of adults aged 65 and older, often making kitchen navigation and independent living difficult, particul

Integration of Deep Reinforcement Learning and Agent-based Simulation to Explore Strategies Counteracting Information Disorder

arXiv:2604.13047v1 Announce Type: cross Abstract: In recent years, the spread of fake news has triggered a growing interest in Information Disorders (ID) on social media, a phenomenon that has become

Internal Knowledge Without External Expression: Probing the Generalization Boundary of a Classical Chinese Language Model

arXiv:2604.14180v1 Announce Type: new Abstract: We train a 318M-parameter Transformer language model from scratch on a curated corpus of 1.56 billion tokens of pure Classical Chinese, with zero Englis

KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality

arXiv:2506.19807v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs), particularly slow-thinking models, often exhibit severe hallucination, outputting incorrect content due to an in

tutorialsarxiv-cs-cl

Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions

arXiv:2502.16761v2 Announce Type: replace Abstract: Large language models (LLMs) present novel opportunities in public opinion research by predicting survey responses in advance during the early stage

Hardware

LayerScope: Predictive Cross-Layer Scheduling for Efficient Multi-Batch MoE Inference on Legacy Servers

arXiv:2509.23638v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models face memory and PCIe latency bottlenecks when deployed on commodity hardware. Offloading expert weights to CPU memor

hardwarearxiv-cs-lg

Learning to Plan, Planning to Learn: Adaptive Hierarchical RL-MPC for Sample-Efficient Decision Making

arXiv:2512.17091v2 Announce Type: replace Abstract: We propose a new approach for solving planning problems with a hierarchical structure, fusing reinforcement learning and MPC planning. Our formulati

tutorialsarxiv-cs-lg

MADE: A Living Benchmark for Multi-Label Text Classification with Uncertainty Quantification of Medical Device Adverse Events

arXiv:2604.15203v1 Announce Type: new Abstract: Machine learning in high-stakes domains such as healthcare requires not only strong predictive performance but also reliable uncertainty quantification

Material-Agnostic Zero-Shot Thermal Inference for Metal Additive Manufacturing via a Parametric PINN Framework

arXiv:2604.14562v1 Announce Type: new Abstract: Accurate thermal modeling in metal additive manufacturing (AM) is essential for understanding the process-structure-performance relationship. While prio

applicationsarxiv-cs-lg

MedVerse: Efficient and Reliable Medical Reasoning via DAG-Structured Parallel Execution

arXiv:2602.07529v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong performance and rapid progress in a wide range of medical reasoning tasks. However, their sequ

researcharxiv-cs-lg

ORBIT: On-policy Exploration-Exploitation for Controllable Multi-Budget Reasoning

arXiv:2601.08310v2 Announce Type: replace Abstract: Recent Large Reasoning Models (LRMs) achieve strong performance by leveraging long-form Chain-of-Thought (CoT) reasoning, but uniformly applying ove

OVT-MLCS: An Online Visual Tool for MLCS Mining from Long or Big Sequences

arXiv:2604.13037v1 Announce Type: cross Abstract: Mining multiple longest common subsequences (extit{MLCS}) from a set of sequences of three or more over a finite alphabet Sigma (a classical NP-hard p

researcharxiv-cs-ai

QU-NLP at ArchEHR-QA 2026: Two-Stage QLoRA Fine-Tuning of Qwen3-4B for Patient-Oriented Clinical Question Answering and Evidence Sentence Alignment

arXiv:2604.14175v1 Announce Type: new Abstract: We present a unified system addressing both Subtask 3 (answer generation) and Subtask 4 (evidence sentence alignment) of the ArchEHR-QA Shared Task. For

safetyarxiv-cs-cl