Search: “llm”

Can Compact Language Models Search Like Agents? Distillation-Guided Policy Optimization for Preserving Agentic RAG Capabilities

arXiv:2508.20324v4 Announce Type: replace Abstract: Reinforcement Learning has emerged as a dominant post-training approach to elicit agentic RAG behaviors such as search and planning from language mo

safetyarxiv-cs-cl

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Model Releases

Can Large Language Models Really Recognize Your Name?

DGX agent

arXiv:2505.14549v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly being used in privacy pipelines to detect and remedy sensitive data leakage. These solutions oft

model-releasesarxiv-cs-ai

28 Apr 2026

Code Broker: A Multi-Agent System for Automated Code Quality Assessment

arXiv:2604.23088v1 Announce Type: cross Abstract: We present Code Broker, a multi agent system built with Google Agent Development Kit ADK that analyses Python code from files, local directories, or G

Credal Concept Bottleneck Models for Epistemic-Aleatoric Uncertainty Decomposition

arXiv:2604.24170v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) predict through human-interpretable concepts, but they typically output point concept probabilities that conflate epist

CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning

arXiv:2601.13262v2 Announce Type: replace Abstract: While large language models (LLMs) have shown to perform well on monolingual mathematical and commonsense reasoning, they remain unreliable for mult

Discovering Agentic Safety Specifications from 1-Bit Danger Signals

arXiv:2604.23210v1 Announce Type: new Abstract: Can large language model agents discover hidden safety objectives through experience alone? We introduce EPO-Safe (Experiential Prompt Optimization for

Agents

Enabling Transparent Cyber Threat Intelligence Combining Large Language Models and Domain Ontologies

arXiv:2509.00081v2 Announce Type: replace-cross Abstract: Effective Cyber Threat Intelligence (CTI) relies upon accurately structured and semantically enriched information extracted from cybersecurity

agentsarxiv-cs-ai

Model Releases

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce

model-releasesarxiv-cs-ai

arXiv:2604.23993v1 Announce Type: cross Abstract: Product mapping, the task of deciding whether two e-commerce listings refer to the same product, is a core problem for price monitoring and channel vi

Evaluation of Pose Estimation Systems for Sign Language Translation

arXiv:2604.24609v1 Announce Type: new Abstract: Many sign language translation (SLT) systems operate on pose sequences instead of raw video to reduce input dimensionality, improve portability, and par

researcharxiv-cs-cl

Explanation Quality Assessment as Ranking with Listwise Rewards

arXiv:2604.24176v1 Announce Type: new Abstract: We reformulate explanation quality assessment as a ranking problem rather than a generation problem. Instead of optimizing models to produce a single 'b

Failure-Centered Runtime Evaluation for Deployed Trilingual Public-Space Agents

arXiv:2604.23990v1 Announce Type: new Abstract: This paper presents PSA-Eval, a failure-centered runtime evaluation framework for deployed trilingual public-space agents. The central claim is that, wh

Agents

Food4All: A Multi-Agent Framework for Real-time Free Food Discovery with Integrated Nutritional Metadata

arXiv:2510.18289v2 Announce Type: replace Abstract: Food insecurity remains a persistent public health emergency in the United States, tightly interwoven with chronic disease, mental illness, and opio

agentsarxiv-cs-cl

Hardware

FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost

arXiv:2604.24073v1 Announce Type: cross Abstract: Modern industrial Deep Learning Recommendation Models typically extract user preferences through the analysis of sequential interaction histories, sub

hardwarearxiv-cs-ai

From Optimization to Prediction: Transformer-Based Path-Flow Estimation to the Traffic Assignment Problem

arXiv:2510.19889v2 Announce Type: replace-cross Abstract: The traffic assignment problem is essential for traffic flow analysis, traditionally solved using mathematical programs under the Equilibrium

GWT: Scalable Optimizer State Compression for Large Language Model Training

arXiv:2501.07237v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse natural language processing benchmarks. However, the es

Hindsight Preference Optimization for Financial Time Series Advisory

arXiv:2604.23988v1 Announce Type: cross Abstract: Time series models predict numbers; decision-makers need advisory -- directional signals with reasoning, actionable suggestions, and risk management.

Human-1 by Josh Talks: A Full-Duplex Conversational Modeling Framework in Hindi using Real-World Conversations

arXiv:2604.23295v1 Announce Type: cross Abstract: Full-duplex spoken dialogue systems can model natural conversational behaviours such as interruptions, overlaps, and backchannels, yet such systems re

applicationsarxiv-cs-ai

Model Releases

Hybrid JIT-CUDA Graph Optimization for Low-Latency Large Language Model Inference

model-releasesarxiv-cs-ai

arXiv:2604.23467v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved strong performance across natural language and multimodal tasks, yet their practical deployment remains con

Improving Robustness of Tabular Retrieval via Representational Stability

arXiv:2604.24040v1 Announce Type: cross Abstract: Transformer-based table retrieval systems flatten structured tables into token sequences, making retrieval sensitive to the choice of serialization ev

Agents

Information-Theoretic Measures in AI: A Practical Decision Guide

arXiv:2604.23716v1 Announce Type: new Abstract: Information-theoretic (IT) measures are ubiquitous in artificial intelligence: entropy drives decision-tree splits and uncertainty quantification, cross

agentsarxiv-cs-ai

Isotonic Layer: A Unified Framework for Recommendation Calibration and Debiasing

arXiv:2603.06589v2 Announce Type: replace-cross Abstract: Model calibration and debiasing are fundamental yet operationally expensive challenges in large-scale recommendation systems. Existing approac

K-Score: Kalman Filter as a Principled Alternative to Reward Normalization in Reinforcement Learning

arXiv:2604.23056v1 Announce Type: cross Abstract: We propose a simple yet effective alternative to reward normalization in policy gradient reinforcement learning by integrating a 1D Kalman filter for

KAConvNet: Kolmogorov-Arnold Convolutional Networks for Vision Recognition

arXiv:2604.23320v1 Announce Type: new Abstract: The Convolutional Neural Networks (CNNs) have been the dominant and effective approach for general computer vision tasks. Recently, Kolmogorov-Arnold ne

safetyarxiv-cs-cv

Knee-xRAI: An Explainable AI Framework for Automatic Kellgren-Lawrence Grading of Knee Osteoarthritis

arXiv:2604.23435v1 Announce Type: cross Abstract: Radiographic grading of knee osteoarthritis (KOA) with the Kellgren-Lawrence (KL) system is limited by inter-reader variability and the opacity of cur

LAMP: Extracting Local Decision Surfaces From Large Language Models

arXiv:2505.11772v3 Announce Type: replace Abstract: We introduce LAMP (Local Attribution Mapping Probe), a method that shines light onto a black-box language model's decision surface and studies how r

local-aiarxiv-cs-lg

Learning Evidence of Depression Symptoms via Prompt Induction

arXiv:2604.24376v1 Announce Type: new Abstract: Depression places substantial pressure on mental health services, and many people describe their experiences outside clinical settings in high-volume us

researcharxiv-cs-cl

Learning to Think from Multiple Thinkers

arXiv:2604.24737v1 Announce Type: cross Abstract: We study learning with Chain-of-Thought (CoT) supervision from multiple thinkers, all of whom provide correct but possibly systematically different so

tutorialsarxiv-cs-ai

LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models

arXiv:2604.23809v1 Announce Type: new Abstract: Small language models (SLMs) are promising for real-world deployment due to their efficiency and low operational cost. However, their limited capacity s

applicationsarxiv-cs-cl

Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning

arXiv:2604.22795v1 Announce Type: cross Abstract: This study presents a multi-agent reinforcement learning (MARL) framework for load-constrained wind farm flow control (WFFC). While wake steering can

local-aiarxiv-cs-lg

MIPIC: Matryoshka Representation Learning via Self-Distilled Intra-Relational and Progressive Information Chaining

arXiv:2604.24374v1 Announce Type: new Abstract: Representation learning is fundamental to NLP, but building embeddings that work well at different computational budgets is challenging. Matryoshka Repr

safetyarxiv-cs-cl

MirrorMark: A Distortion-Free Multi-Bit Watermark for Large Language Models

arXiv:2601.22246v2 Announce Type: replace-cross Abstract: As large language models (LLMs) become integral to applications such as question answering and content creation, reliable content attribution

MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedback

arXiv:2604.23107v1 Announce Type: cross Abstract: Causal effect estimation from observational data requires careful adjustment for confounding. Classical estimators such as inverse probability weighti

applicationsarxiv-cs-lg

Modeling Behavioral Intensity and Transitions for Generative Recommendation

arXiv:2604.24472v1 Announce Type: cross Abstract: Multi-behavior recommendation aims to predict user conversions by modeling various interaction types that carry distinct intent signals. Recently, gen

NeSyCat: A Monad-Based Categorical Semantics of the Neurosymbolic ULLER Framework

arXiv:2604.24612v1 Announce Type: new Abstract: ULLER (Unified Language for LEarning and Reasoning) offers a unified first-order logic (FOL) syntax, enabling its knowledge bases to be used directly ac

Preserving Long-Tailed Expert Information in Mixture-of-Experts Tuning

arXiv:2604.23036v1 Announce Type: cross Abstract: Despite MoE models leading many benchmarks, supervised fine-tuning (SFT) for the MoE architectures remains difficult because its router layers are fra

safetyarxiv-cs-cl

Probing Visual Planning in Image Editing Models

arXiv:2604.22868v1 Announce Type: cross Abstract: Visual planning represents a crucial facet of human intelligence, especially in tasks that require complex spatial reasoning and navigation. Yet, in m

tutorialsarxiv-cs-ai

Propagation Structure-Semantic Transfer Learning for Robust Fake News Detection

arXiv:2604.23974v1 Announce Type: new Abstract: Fake news generally refers to false information that is spread deliberately to deceive people, which has detrimental social effects. Existing fake news

tutorialsarxiv-cs-cl

Protecting the Trace: A Principled Black-Box Approach Against Distillation Attacks

arXiv:2604.23238v1 Announce Type: cross Abstract: Frontier models push the boundaries of what is learnable at extreme computational costs, yet distillation via sampling reasoning traces exposes closed

ReFinE: Streamlining UI Mockup Iteration with Research Findings

arXiv:2604.04353v2 Announce Type: replace-cross Abstract: Although HCI research papers offer valuable design insights, designers often struggle to apply them in design workflows due to difficulties in

tutorialsarxiv-cs-ai

Reliable Microservice Tail Latency Prediction via Decoupled Dual-Stream Learning and Gradient Modulation

arXiv:2508.01635v2 Announce Type: replace-cross Abstract: Microservice architectures enable scalable cloud-native applications; however, the distributed nature of these systems complicates the mainten

Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis

arXiv:2604.24198v1 Announce Type: cross Abstract: Process Reward Models (PRMs) have achieved remarkable success in augmenting the reasoning capabilities of Large Language Models (LLMs) within static d

S^2IT: Stepwise Syntax Integration Tuning for Large Language Models in Aspect Sentiment Quad Prediction

arXiv:2604.23296v1 Announce Type: cross Abstract: Aspect Sentiment Quad Prediction (ASQP) has seen significant advancements, largely driven by the powerful semantic understanding and generative capabi

SAGE: Sparse Adaptive Guidance for Dependency-Aware Tabular Data Generation

arXiv:2604.24368v1 Announce Type: new Abstract: Generating high-fidelity synthetic tabular data remains a critical challenge for enhancing data availability in privacy-sensitive and low-resource domai

safetyarxiv-cs-lg

Scalable Explainability-as-a-Service (XaaS) for Edge AI Systems

arXiv:2602.04120v2 Announce Type: replace-cross Abstract: Though Explainable AI (XAI) has made significant advancements, its inclusion in edge and IoT systems is typically ad-hoc and inefficient. Most

Hardware

Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models

arXiv:2604.24708v1 Announce Type: cross Abstract: Training large neural networks with data-parallel stochastic gradient descent allocates N GPU replicas to compute effectively identical updates -- a p

hardwarearxiv-cs-ai

SemML 2.0: Synthesizing Controllers for LTL

arXiv:2604.24102v1 Announce Type: new Abstract: Synthesizing a reactive system from specifications given in linear temporal logic (LTL) is a classical problem, finding its applications in safety-criti

Sparse Concept Anchoring for Interpretable and Controllable Neural Representations

arXiv:2512.12469v3 Announce Type: replace Abstract: We introduce Sparse Concept Anchoring, a method that biases latent space to position a targeted subset of concepts while allowing others to self-org

researcharxiv-cs-lg

Talking Slide Avatars: Open-Source Multimodal Communication Approach for Teaching

arXiv:2604.23703v1 Announce Type: cross Abstract: Slide-based teaching is widely used in higher education, yet in online, hybrid, and asynchronous contexts, slides often lose the instructor presence,

applicationsarxiv-cs-ai