Search: “llm”

NaviRAG: Towards Active Knowledge Navigation for Retrieval-Augmented Generation

arXiv:2604.12766v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) typically relies on a flat retrieval paradigm that maps queries directly to static, isolated text segments. This ap

agentsarxiv-cs-cl

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Obtaining Partition Crossover masks using Statistical Linkage Learning for solving noised optimization problems with hidden variable dependency structure

DGX agent

arXiv:2604.11862v1 Announce Type: cross Abstract: In optimization problems, some variable subsets may have a joint non-linear or non-monotonical influence on the function value. Therefore, knowledge o

applicationsarxiv-cs-lg

15 Apr 2026

OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning

arXiv:2502.11271v2 Announce Type: replace-cross Abstract: Solving complex reasoning tasks may involve visual understanding, domain knowledge retrieval, numerical calculation, and multi-step reasoning.

agentsarxiv-cs-cl

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Relaxing Anchor-Frame Dominance for Mitigating Hallucinations in Video Large Language Models

arXiv:2604.12582v1 Announce Type: new Abstract: Recent Video Large Language Models (Video-LLMs) have demonstrated strong capability in video understanding, yet they still suffer from hallucinations. E

safetyarxiv-cs-cv

Revisiting the Reliability of Language Models in Instruction-Following

arXiv:2512.14754v2 Announce Type: replace-cross Abstract: Advanced LLMs have achieved near-ceiling instruction-following accuracy on benchmarks such as IFEval. However, these impressive scores do not

ROSE: An Intent-Centered Evaluation Metric for NL2SQL

arXiv:2604.12988v1 Announce Type: cross Abstract: Execution Accuracy (EX), the widely used metric for evaluating the effectiveness of Natural Language to SQL (NL2SQL) solutions, is becoming increasing

SCRIPT: A Subcharacter Compositional Representation Injection Module for Korean Pre-Trained Language Models

arXiv:2604.12377v1 Announce Type: cross Abstract: Korean is a morphologically rich language with a featural writing system in which each character is systematically composed of subcharacter units know

SEW: Self-Evolving Agentic Workflows for Automated Code Generation

arXiv:2505.18646v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated effectiveness in code generation tasks. To enable LLMs to address more complex coding challenge

SIR-Bench: Evaluating Investigation Depth in Security Incident Response Agents

arXiv:2604.12040v1 Announce Type: cross Abstract: We present SIR-Bench, a benchmark of 794 test cases for evaluating autonomous security incident response agents that distinguishes genuine forensic in

SIRI-Bench: Challenging VLMs' Spatial Intelligence through Complex Reasoning Tasks

model-releasesarxiv-cs-cv

arXiv:2506.14512v4 Announce Type: replace Abstract: Large Language Models (LLMs) have undergone rapid progress, largely attributed to reinforcement learning on complex reasoning tasks. In contrast, wh

Think Through Uncertainty: Improving Long-Form Generation Factuality via Reasoning Calibration

arXiv:2604.12046v1 Announce Type: new Abstract: Large language models (LLMs) often hallucinate in long-form generation. Existing approaches mainly improve factuality through post-hoc revision or reinf

Towards EnergyGPT: A Large Language Model Specialized for the Energy Sector

arXiv:2509.07177v3 Announce Type: replace Abstract: Large language models have demonstrated impressive capabilities across various domains. However, their general-purpose nature often limits their eff

ToxiTrace: Gradient-Aligned Training for Explainable Chinese Toxicity Detection

arXiv:2604.12321v1 Announce Type: new Abstract: Existing Chinese toxic content detection methods mainly target sentence-level classification but often fail to provide readable and contiguous toxic evi

Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving

arXiv:2604.12208v1 Announce Type: cross Abstract: Global navigation information and local scene understanding are two crucial components of autonomous driving systems. However, our experimental result

local-aiarxiv-cs-ai

WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering

arXiv:2604.05818v2 Announce Type: replace-cross Abstract: Multi-modal Retrieval-Augmented Generation (RAG) has emerged as a highly effective paradigm for Knowledge-Based Visual Question Answering (KB-

A Benchmark for Gap and Overlap Analysis as a Test of KG Task Readiness

arXiv:2604.10853v1 Announce Type: new Abstract: Task-oriented evaluation of knowledge graph (KG) quality increasingly asks whether an ontology-based representation can answer the competency questions

A Complete Decomposition of KL Error using Refined Information and Mode Interaction Selection

arXiv:2410.11964v2 Announce Type: replace Abstract: The log-linear model has received a significant amount of theoretical attention in previous decades and remains the fundamental tool used for learni

applicationsarxiv-cs-lg

Tutorials

A Mechanistic Analysis of Looped Reasoning Language Models

arXiv:2604.11791v1 Announce Type: cross Abstract: Reasoning has become a central capability in large language models. Recent research has shown that reasoning performance can be improved by looping an

tutorialsarxiv-cs-ai

Advancing Polish Language Modeling through Tokenizer Optimization in the Bielik v3 7B and 11B Series

arXiv:2604.10799v1 Announce Type: cross Abstract: The development of the Bielik v3 PL series, encompassing both the 7B and 11B parameter variants, represents a significant milestone in the field of la

Agri-R1: Agricultural Reasoning for Disease Diagnosis via Automated-Synthesis and Reinforcement Learning

arXiv:2601.04672v2 Announce Type: replace-cross Abstract: Agricultural disease diagnosis challenges VLMs, as conventional fine-tuning requires extensive labels, lacks interpretability, and generalizes

Ambiguity Detection and Elimination in Automated Executable Process Modeling

arXiv:2604.10884v1 Announce Type: cross Abstract: Automated generation of executable Business Process Model and Notation (BPMN) models from natural-language specifications is increasingly enabled by l

local-aiarxiv-cs-ai

Automating Structural Analysis Across Multiple Software Platforms Using Large Language Models

arXiv:2604.09866v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have shown the promise to significantly accelerate the workflow by automating structural modeling and

agentsarxiv-cs-ai

AutoMS: Multi-Agent Evolutionary Search for Cross-Physics Inverse Microstructure Design

arXiv:2603.27195v2 Announce Type: replace Abstract: Designing microstructures with coupled cross-physics objectives is a fundamental challenge where traditional topology optimization is often computat

Back to Basics: Let Conversational Agents Remember with Just Retrieval and Generation

arXiv:2604.11628v1 Announce Type: new Abstract: Existing conversational memory systems rely on complex hierarchical summarization or reinforcement learning to manage long-term dialogue history, yet re

BankerToolBench: Evaluating AI Agents in End-to-End Investment Banking Workflows

arXiv:2604.11304v1 Announce Type: new Abstract: Existing AI benchmarks lack the fidelity to assess economically meaningful progress on professional workflows. To evaluate frontier AI agents in a high-

Beyond Black-Box Interventions: Latent Probing for Faithful Retrieval-Augmented Generation

arXiv:2510.12460v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems often fail to maintain contextual faithfulness, generating responses that conflict with the provided co

BlasBench: An Open Benchmark for Irish Speech Recognition

arXiv:2604.10736v1 Announce Type: new Abstract: No open Irish-specific benchmark compares end-user ASR systems under a shared Irish-aware evaluation protocol. To solve this, we release BlasBench, an o

CAGE: Bridging the Accuracy-Aesthetics Gap in Educational Diagrams via Code-Anchored Generative Enhancement

arXiv:2604.09691v1 Announce Type: cross Abstract: Educational diagrams -- labeled illustrations of biological processes, chemical structures, physical systems, and mathematical concepts -- are essenti

Tutorials

Can Small Training Runs Reliably Guide Data Curation? Rethinking Proxy-Model Practice

arXiv:2512.24503v2 Announce Type: replace-cross Abstract: Data teams at frontier AI companies routinely train small proxy models to make critical decisions about pretraining data recipes for full-scal

tutorialsarxiv-cs-ai

CheeseBench: Evaluating Large Language Models on Rodent Behavioral Neuroscience Paradigms

arXiv:2604.10825v1 Announce Type: new Abstract: We introduce CheeseBench, a benchmark that evaluates large language models (LLMs) on nine classical behavioral neuroscience paradigms (Morris water maze

ClaimDB: A Fact Verification Benchmark over Large Structured Data

arXiv:2601.14698v2 Announce Type: replace Abstract: Real-world fact-checking often involves verifying claims grounded in structured data at scale. Despite substantial progress in fact-verification ben

CLSGen: A Dual-Head Fine-Tuning Framework for Joint Probabilistic Classification and Verbalized Explanation

arXiv:2604.11801v1 Announce Type: new Abstract: With the recent progress of Large Language Models (LLMs), there is a growing interest in applying these models to solve complex and challenging problems

CodeComp: Structural KV Cache Compression for Agentic Coding

arXiv:2604.10235v1 Announce Type: new Abstract: Agentic code tasks such as fault localization and patch generation require processing long codebases under tight memory constraints, where the Key-Value

local-aiarxiv-cs-cl

COMPOSITE-Stem

arXiv:2604.09836v1 Announce Type: new Abstract: AI agents hold growing promise for accelerating scientific discovery; yet, a lack of frontier evaluations hinders adoption into real workflows. Expert-w

Computational Implementation of a Model of Category-Theoretic Metaphor Comprehension

arXiv:2604.10035v1 Announce Type: cross Abstract: In this study, we developed a computational implementation for a model of metaphor comprehension based on the theory of indeterminate natural transfor

DarwinNet: An Evolutionary Network Architecture for Agent-Driven Protocol Synthesis

arXiv:2604.01236v2 Announce Type: replace-cross Abstract: Traditional network architectures suffer from severe protocol ossification and structural fragility due to their reliance on static, human-def

agentsarxiv-cs-ai

Deconstructing Subset Construction -- Reducing While Determinizing

arXiv:2505.10319v2 Announce Type: replace-cross Abstract: We present a novel perspective on the NFA canonization problem, which introduces intermediate minimization steps to reduce the exploration spa

applicationsarxiv-cs-lg

DeCoVec: Building Decoding Space based Task Vector for Large Language Models via In-Context Learning

arXiv:2604.11129v1 Announce Type: new Abstract: Task vectors, representing directions in model or activation spaces that encode task-specific behaviors, have emerged as a promising tool for steering l

Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation

arXiv:2604.10741v1 Announce Type: cross Abstract: Recent agentic search frameworks enable deep research via iterative planning and retrieval, reducing hallucinations and enhancing factual grounding. H

local-aiarxiv-cs-ai

Safety

Demographic and Linguistic Bias Evaluation in Omnimodal Language Models

arXiv:2604.10014v1 Announce Type: cross Abstract: This paper provides a comprehensive evaluation of demographic and linguistic biases in omnimodal language models that process text, images, audio, and

safetyarxiv-cs-ai

Detecting Corporate AI-Washing via Cross-Modal Semantic Inconsistency Learning

arXiv:2604.09644v1 Announce Type: cross Abstract: Corporate AI-washing-the strategic misrepresentation of AI capabilities via exaggerated or fabricated cross-channel disclosures-has emerged as a syste

Different types of syntactic agreement recruit the same units within large language models

arXiv:2512.03676v2 Announce Type: replace Abstract: Large language models (LLMs) can reliably distinguish grammatical from ungrammatical sentences, but how grammatical knowledge is represented within

local-aiarxiv-cs-cl

Discourse Coherence and Response-Guided Context Rewriting for Multi-Party Dialogue Generation

arXiv:2604.06784v2 Announce Type: replace Abstract: Previous research on multi-party dialogue generation has predominantly leveraged structural information inherent in dialogues to directly inform the

Does Your VFM Speak Plant? The Botanical Grammar of Vision Foundation Models for Object Detection

arXiv:2604.09920v1 Announce Type: new Abstract: Vision foundation models (VFMs) offer the promise of zero-shot object detection without task-specific training data, yet their performance in complex ag

applicationsarxiv-cs-cv

Domain-Specific Data Generation Framework for RAG Adaptation

arXiv:2510.11217v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) combines the language understanding and reasoning power of large language models (LLMs) with external ret

applicationsarxiv-cs-ai

Tutorials

Dynamic Summary Generation for Interpretable Multimodal Depression Detection

arXiv:2604.11334v1 Announce Type: new Abstract: Depression remains widely underdiagnosed and undertreated because stigma and subjective symptom ratings hinder reliable screening. To address this chall

tutorialsarxiv-cs-ai

EduIllustrate: Towards Scalable Automated Generation Of Multimodal Educational Content

arXiv:2604.05005v2 Announce Type: replace-cross Abstract: Large language models are increasingly used as educational assistants, yet evaluation of their educational capabilities remains concentrated o

Safety

EE-MCP: Self-Evolving MCP-GUI Agents via Automated Environment Generation and Experience Learning

arXiv:2604.09815v1 Announce Type: new Abstract: Computer-use agents that combine GUI interaction with structured API calls via the Model Context Protocol (MCP) show promise for automating software tas

safetyarxiv-cs-ai