Search: “llm”

Defining and Evaluation Method for External Human-Machine Interfaces

arXiv:2604.12293v1 Announce Type: new Abstract: As the number of fatalities involving Autonomous Vehicles increase, the need for a universal method of communicating between vehicles and other agents o

agentsarxiv-cs-ro

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Designing for Error Recovery in Human-Robot Interaction

DGX agent

arXiv:2604.12473v1 Announce Type: new Abstract: This position paper looks briefly at the way we attempt to program robotic AI systems. Many AI systems are based on the idea of trying to improve the pe

tutorialsarxiv-cs-ro

15 Apr 2026

Does RLVR Extend Reasoning Boundaries? Investigating Capability Expansion in Vision-Language Models

arXiv:2511.00710v4 Announce Type: replace Abstract: Recent studies posit that Reinforcement Learning with Verifiable Rewards (RLVR) primarily amplifies behaviors inherent to the pre-training distribut

El Agente Quntur: A research collaborator agent for quantum chemistry

arXiv:2602.04850v2 Announce Type: replace-cross Abstract: Quantum chemistry is a foundational enabling tool for the fields of chemistry, materials science, computational biology and others. Despite of

Enhancing Agentic Textual Graph Retrieval with Synthetic Stepwise Supervision

arXiv:2510.03323v2 Announce Type: replace Abstract: Integrating textual graphs into Large Language Models (LLMs) is promising for complex graph-based QA. However, a key bottleneck is retrieving inform

safetyarxiv-cs-cl

Applications

Enhancing Clustering: An Explainable Approach via Filtered Patterns

arXiv:2604.12460v1 Announce Type: new Abstract: Machine learning has become a central research area, with increasing attention devoted to explainable clustering, also known as conceptual clustering, w

applicationsarxiv-cs-ai

Local Ai

Evaluating Language Models for Harmful Manipulation

arXiv:2603.25326v4 Announce Type: replace Abstract: Interest in the concept of AI-driven harmful manipulation is growing, yet current approaches to evaluating it are limited. This paper introduces a f

local-aiarxiv-cs-ai

FABLE: Fine-grained Fact Anchoring for Unstructured Model Editing

model-releasesarxiv-cs-cl

arXiv:2604.12559v1 Announce Type: new Abstract: Unstructured model editing aims to update models with real-world text, yet existing methods often memorize text holistically without reliable fine-grain

Fine-tuning Factor Augmented Neural Lasso for Heterogeneous Environments

model-releasesarxiv-cs-lg

arXiv:2604.12288v1 Announce Type: cross Abstract: Fine-tuning is a widely used strategy for adapting pre-trained models to new tasks, yet its methodology and theoretical properties in high-dimensional

GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization

arXiv:2604.11810v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation. However, their immense number

Heuristic Classification of Thoughts Prompting (HCoT): Integrating Expert System Heuristics for Structured Reasoning into Large Language Models

arXiv:2604.12390v1 Announce Type: new Abstract: This paper addresses two limitations of large language models (LLMs) in solving complex problems: (1) their reasoning processes exhibit Bayesian-like st

tutorialsarxiv-cs-ai

Applications

Influence Strength Estimation in Hyperbolic Space for Social Influence Maximization

arXiv:2502.13571v2 Announce Type: replace-cross Abstract: The Influence Maximization (IM) problem aims to find a small set of influential users to maximize their influence spread in a social network.

applicationsarxiv-cs-lg

Instructions are all you need: Self-supervised Reinforcement Learning for Instruction Following

arXiv:2510.14420v4 Announce Type: replace-cross Abstract: Language models often struggle to follow multi-constraint instructions that are crucial for real-world applications. Existing reinforcement le

Iterative Compositional Data Generation for Robot Control

arXiv:2512.10891v4 Announce Type: replace-cross Abstract: Collecting robotic manipulation data is expensive, making it impractical to acquire demonstrations for the combinatorially large space of task

tutorialsarxiv-cs-lg

KG-Reasoner: A Reinforced Model for End-to-End Multi-Hop Knowledge Graph Reasoning

arXiv:2604.12487v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit strong abilities in natural language understanding and generation, yet they struggle with knowledge-intensive rea

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain

arXiv:2510.05159v4 Announce Type: replace-cross Abstract: While finetuning AI agents on interaction data -- such as web browsing or tool use -- improves their capabilities, it also introduces critical

Modality-Native Routing in Agent-to-Agent Networks: A Multimodal A2A Protocol Extension

arXiv:2604.12213v1 Announce Type: new Abstract: Preserving multimodal signals across agent boundaries is necessary for accurate cross-modal reasoning, but it is not sufficient. We show that modality-n

Local Ai

MoDora: Tree-Based Semi-Structured Document Analysis System

arXiv:2602.23061v3 Announce Type: replace-cross Abstract: Semi-structured documents integrate diverse interleaved data elements (e.g., tables, charts, hierarchical paragraphs) arranged in various and

local-aiarxiv-cs-ai

M^star: Every Task Deserves Its Own Memory Harness

arXiv:2604.11811v1 Announce Type: cross Abstract: Large language model agents rely on specialized memory systems to accumulate and reuse knowledge during extended interactions. Recent architectures ty

MultiDocFusion: Hierarchical and Multimodal Chunking Pipeline for Enhanced RAG on Long Industrial Documents

arXiv:2604.12352v1 Announce Type: new Abstract: RAG-based QA has emerged as a powerful method for processing long industrial documents. However, conventional text chunking approaches often neglect com

Parallax: Why AI Agents That Think Must Never Act

arXiv:2604.12986v1 Announce Type: cross Abstract: Autonomous AI agents are rapidly transitioning from experimental tools to operational infrastructure, with projections that 80% of enterprise applicat

PubSwap: Public-Data Off-Policy Coordination for Federated RLVR

arXiv:2604.12160v1 Announce Type: new Abstract: Reasoning post-training with reinforcement learning from verifiable rewards (RLVR) is typically studied in centralized settings, yet many realistic appl

safetyarxiv-cs-lg

RACF: A Resilient Autonomous Car Framework with Object Distance Correction

arXiv:2604.12418v1 Announce Type: cross Abstract: Autonomous vehicles are increasingly deployed in safety-critical applications, where sensing failures or cyberphysical attacks can lead to unsafe oper

Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework

arXiv:2509.18127v3 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) enable interpretability research by decomposing entangled model activations into monosemantic features. However, un

Scaffold-Conditioned Preference Triplets for Controllable Molecular Optimization with Large Language Models

arXiv:2604.12350v1 Announce Type: cross Abstract: Molecular property optimization is central to drug discovery, yet many deep learning methods rely on black-box scoring and offer limited control over

SceneCritic: A Symbolic Evaluator for 3D Indoor Scene Synthesis

arXiv:2604.13035v1 Announce Type: cross Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) increasingly generate indoor scenes through intermediate structures such as layouts and

researcharxiv-cs-cl

SDFed: Bridging Local Global Discrepancy via Subspace Refinement and Divergence Control in Federated Prompt Learning

arXiv:2602.08590v4 Announce Type: replace Abstract: Vision-language pretrained models offer strong transferable representations, yet adapting them in privacy-sensitive multi-party settings is challeng

tutorialsarxiv-cs-lg

Security and Resilience in Autonomous Vehicles: A Proactive Design Approach

arXiv:2604.12408v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) promise efficient, clean and cost-effective transportation systems, but their reliance on sensors, wireless communications,

SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration

arXiv:2604.12247v1 Announce Type: cross Abstract: Speculative decoding has emerged as a promising approach to accelerate autoregressive inference in large language models (LLMs). Self-draft methods, w

The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap

arXiv:2604.11828v1 Announce Type: new Abstract: Science is widely regarded as humanity's most reliable method for uncovering truths about the natural world. Yet the trajectory of scientific discovery

Thinking Sparks!: Emergent Attention Heads in Reasoning Models During Post Training

arXiv:2509.25758v2 Announce Type: replace Abstract: The remarkable capabilities of modern large reasoning models are largely unlocked through post-training techniques such as supervised fine-tuning (S

Toward Autonomous Long-Horizon Engineering for ML Research

arXiv:2604.13018v1 Announce Type: new Abstract: Autonomous AI research has advanced rapidly, but long-horizon ML research engineering remains difficult: agents must sustain coherent progress across ta

agentsarxiv-cs-cl

TRUST Agents: A Collaborative Multi-Agent Framework for Fake News Detection, Explainable Verification, and Logic-Aware Claim Reasoning

arXiv:2604.12184v1 Announce Type: new Abstract: TRUST Agents is a collaborative multi-agent framework for explainable fact verification and fake news detection. Rather than treating verification as a

Using Learning Progressions to Guide AI Feedback for Science Learning

arXiv:2603.03249v2 Announce Type: replace Abstract: Generative artificial intelligence (AI) offers scalable support for formative feedback, yet most AI-generated feedback relies on task-specific rubri

tutorialsarxiv-cs-cl

Variation in Verification: Understanding Verification Dynamics in Large Language Models

arXiv:2509.17995v2 Announce Type: replace-cross Abstract: Recent advances have shown that scaling test-time computation enables large language models (LLMs) to solve increasingly complex problems acro

Hardware

VFA: Relieving Vector Operations in Flash Attention with Global Maximum Pre-computation

arXiv:2604.12798v1 Announce Type: cross Abstract: FlashAttention-style online softmax enables exact attention computation with linear memory by streaming score tiles through on-chip memory and maintai

hardwarearxiv-cs-ai

Local Ai

VideoFlexTok: Flexible-Length Coarse-to-Fine Video Tokenization

arXiv:2604.12887v1 Announce Type: new Abstract: Visual tokenizers map high-dimensional raw pixels into a compressed representation for downstream modeling. Beyond compression, tokenizers dictate what

local-aiarxiv-cs-cv

WebChain: A Large-Scale Human-Annotated Dataset of Real-World Web Interaction Traces

arXiv:2603.05295v3 Announce Type: replace Abstract: We introduce WebChain, the largest open-source dataset of human-annotated trajectories on real-world websites, designed to accelerate reproducible r

3D-Anchored Lookahead Planning for Persistent Robotic Scene Memory via World-Model-Based MCTS

arXiv:2604.11302v1 Announce Type: cross Abstract: We present 3D-Anchored Lookahead Planning (3D-ALP), a System 2 reasoning engine for robotic manipulation that combines Monte Carlo Tree Search (MCTS)

A collaborative agent with two lightweight synergistic models for autonomous crystal materials research

arXiv:2604.11540v1 Announce Type: new Abstract: Current large language models require hundreds of billions of parameters yet struggle with domain-specific reasoning and tool coordination in materials

A molecular clock for writing systems reveals the quantitative impact of imperial power on cultural evolution

arXiv:2604.10957v1 Announce Type: cross Abstract: Writing systems are cultural replicators whose evolution has never been studied quantitatively at global scale. We compile the Global Script Database

ACE-Bench: A Lightweight Benchmark for Evaluating Azure SDK Usage Correctness

arXiv:2604.09564v1 Announce Type: cross Abstract: We present ACE-Bench (Azure SDK Coding Evaluation Benchmark), an execution-free benchmark that provides fast, reproducible pass or fail signals for wh

ACE-TA: An Agentic Teaching Assistant for Grounded Q&A, Quiz Generation, and Code Tutoring

arXiv:2604.09572v1 Announce Type: cross Abstract: We introduce ACE-TA, the Agentic Coding and Explanations Teaching Assistant framework, that autonomously routes conceptual queries drawn from programm

ActDistill: General Action-Guided Self-Derived Distillation for Efficient Vision-Language-Action Models

arXiv:2511.18082v3 Announce Type: replace Abstract: Recent Vision-Language-Action (VLA) models have shown impressive flexibility and generalization, yet their deployment in robotic manipulation remain

tutorialsarxiv-cs-cv

Adaptive Multi-Expert Reasoning via Difficulty-Aware Routing and Uncertainty-Guided Aggregation

arXiv:2604.10335v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong performance in math reasoning benchmarks, but their performance varies inconsistently across problems wi

researcharxiv-cs-cl

Agentic Driving Coach: Robustness and Determinism of Agentic AI-Powered Human-in-the-Loop Cyber-Physical Systems

arXiv:2604.11705v1 Announce Type: new Abstract: Foundation models, including large language models (LLMs), are increasingly used for human-in-the-loop (HITL) cyber-physical systems (CPS) because found

AI Integrity: A New Paradigm for Verifiable AI Governance

arXiv:2604.11065v1 Announce Type: new Abstract: AI systems increasingly shape high-stakes decisions in healthcare, law, defense, and education, yet existing governance paradigms -- AI Ethics, AI Safet

ArtiCAD: Articulated CAD Assembly Design via Multi-Agent Code Generation

arXiv:2604.10992v1 Announce Type: new Abstract: Parametric Computer-Aided Design (CAD) of articulated assemblies is essential for product development, yet generating these multi-part, movable models f

agentsarxiv-cs-cv