Search: “papers”

Teaching an Agent to Sketch One Part at a Time

arXiv:2603.19500v2 Announce Type: replace Abstract: We develop a method for producing vector sketches one part at a time. To do this, we train a multi-modal language model-based agent using a novel mu

27 Apr 2026

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

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DGX agent

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

researcharxiv-cs-cl

24 Apr 2026

PosterForest: Hierarchical Multi-Agent Collaboration for Scientific Poster Generation

arXiv:2508.21720v2 Announce Type: replace Abstract: Automating scientific poster generation requires hierarchical document understanding and coherent content-layout planning. Existing methods often re

RewardBench 2: Advancing Reward Model Evaluation

arXiv:2506.01937v2 Announce Type: replace Abstract: Reward models are used throughout the post-training of language models to capture nuanced signals from preference data and provide a training target

Scaling of Gaussian Kolmogorov--Arnold Networks

arXiv:2604.21174v1 Announce Type: cross Abstract: The Gaussian scale parameter (epsilon) is central to the behavior of Gaussian Kolmogorov--Arnold Networks (KANs), yet its role in deep edge-based arch

Verifying Machine Learning Interpretability Requirements through Provenance

arXiv:2604.21599v1 Announce Type: cross Abstract: Machine Learning (ML) Engineering is a growing field that necessitates an increase in the rigor of ML development. It draws many ideas from software e

Artifacts of Numerical Integration in Learning Dynamical Systems

arXiv:2507.14491v3 Announce Type: replace-cross Abstract: In many applications, one needs to learn a dynamical system from its solutions sampled at a finite number of time points. The learning problem

agentsarxiv-cs-lg

Relative Principals, Pluralistic Alignment, and the Structural Value Alignment Problem

arXiv:2604.20805v1 Announce Type: cross Abstract: The value alignment problem for artificial intelligence (AI) is often framed as a purely technical or normative challenge, sometimes focused on hypoth

safetyarxiv-cs-ai

RExBench: Can coding agents autonomously implement AI research extensions?

arXiv:2506.22598v3 Announce Type: replace Abstract: Agents based on Large Language Models (LLMs) have shown promise for performing sophisticated software engineering tasks autonomously. In addition, t

Towards Explainable Federated Learning: Understanding the Impact of Differential Privacy

arXiv:2602.10100v2 Announce Type: replace Abstract: Data privacy and eXplainable Artificial Intelligence (XAI) are two important aspects for modern Machine Learning systems. To enhance data privacy, r

Construction of Knowledge Graph based on Language Model

arXiv:2604.19137v1 Announce Type: new Abstract: Knowledge Graph (KG) can effectively integrate valuable information from massive data, and thus has been rapidly developed and widely used in many field

researcharxiv-cs-cl

From Natural Language to Executable Narsese: A Neuro-Symbolic Benchmark and Pipeline for Reasoning with NARS

arXiv:2604.18873v1 Announce Type: new Abstract: Large language models (LLMs) are highly capable at language generation, but they remain unreliable when reasoning requires explicit symbolic structure,

Tutorials

Multi-Cycle Spatio-Temporal Adaptation in Human-Robot Teaming

arXiv:2604.19670v1 Announce Type: cross Abstract: Effective human-robot teaming is crucial for the practical deployment of robots in human workspaces. However, optimizing joint human-robot plans remai

tutorialsarxiv-cs-ai

OMAC: A Holistic Optimization Framework for LLM-Based Multi-Agent Collaboration

arXiv:2505.11765v3 Announce Type: replace-cross Abstract: Agents powered by advanced large language models (LLMs) have demonstrated impressive capabilities across diverse complex applications. Recentl

Local Ai

Optimal Routing for Federated Learning over Dynamic Satellite Networks: Tractable or Not?

arXiv:2604.19399v1 Announce Type: new Abstract: Federated learning (FL) is a key paradigm for distributed model learning across decentralized data sources. Communication in each FL round typically con

local-aiarxiv-cs-lg

Regulating Artificial Intimacy: From Locks and Blocks to Relational Accountability

arXiv:2604.18893v1 Announce Type: cross Abstract: A series of high-profile tragedies involving companion chatbots has triggered an unusually rapid regulatory response. Several jurisdictions, including

safetyarxiv-cs-ai

Revisiting RaBitQ and TurboQuant: A Symmetric Comparison of Methods, Theory, and Experiments

arXiv:2604.19528v1 Announce Type: cross Abstract: This technical note revisits the relationship between RaBitQ and TurboQuant under a unified comparison framework. We compare the two methods in terms

RoLegalGEC: Legal Domain Grammatical Error Detection and Correction Dataset for Romanian

arXiv:2604.19593v1 Announce Type: cross Abstract: The importance of clear and correct text in legal documents cannot be understated, and, consequently, a grammatical error correction tool meant to ass

applicationsarxiv-cs-ai

CHIMERA: A Knowledge Base of Scientific Idea Recombinations for Research Analysis and Ideation

arXiv:2505.20779v5 Announce Type: replace Abstract: A hallmark of human innovation is recombination -- the creation of novel ideas by integrating elements from existing concepts and mechanisms. In thi

researcharxiv-cs-cl

COFFAIL: A Dataset of Successful and Anomalous Robot Skill Executions in the Context of Coffee Preparation

arXiv:2604.18236v1 Announce Type: new Abstract: In the context of robot learning for manipulation, curated datasets are an important resource for advancing the state of the art; however, available dat

safetyarxiv-cs-ro

Common Corpus: The Largest Collection of Ethical Data for LLM Pre-Training

arXiv:2506.01732v2 Announce Type: replace Abstract: Large Language Models (LLMs) are pre-trained on large data from different sources and domains. These datasets often contain trillions of tokens, inc

applicationsarxiv-cs-cl

From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models

arXiv:2603.04592v3 Announce Type: replace Abstract: Standard Large Language Models (LLMs) are predominantly designed for static inference with pre-defined inputs, which limits their applicability in d

applicationsarxiv-cs-cl

Matlas: A Semantic Search Engine for Mathematics

arXiv:2604.17484v1 Announce Type: cross Abstract: Retrieving mathematical knowledge is a central task in both human-driven research, such as determining whether a result already exists, finding relate

Matrix: Peer-to-Peer Multi-Agent Synthetic Data Generation Framework

arXiv:2511.21686v2 Announce Type: replace Abstract: Synthetic data has become increasingly important for training large language models, especially when real data is scarce, expensive, or privacy-sens

agentsarxiv-cs-cl

ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition

arXiv:2503.21248v3 Announce Type: replace Abstract: Large language models (LLMs) have shown potential in assisting scientific research, yet their ability to discover high-quality research hypotheses r

R&F-Inventory: A Large-Scale Dataset for Monotonic Inventory Estimation in Reach and Frequency Advertising

arXiv:2604.16821v1 Announce Type: new Abstract: Reach and Frequency (R&F) contract advertising is an important form of widely used brand advertising. Unlike performance advertising, R&F contracts emph

SciImpact: A Multi-Dimensional, Multi-Field Benchmark for Scientific Impact Prediction

arXiv:2604.17141v1 Announce Type: new Abstract: The rapid growth of scientific literature calls for automated methods to assess and predict research impact. Prior work has largely focused on citation-

SeekerGym: A Benchmark for Reliable Information Seeking

arXiv:2604.17143v1 Announce Type: new Abstract: Despite their substantial successes, AI agents continue to face fundamental challenges in terms of trustworthiness. Consider deep research agents, taske

Local Ai

Video-Robin: Autoregressive Diffusion Planning for Intent-Grounded Video-to-Music Generation

arXiv:2604.17656v1 Announce Type: cross Abstract: Video-to-music (V2M) is the fundamental task of creating background music for an input video. Recent V2M models achieve audiovisual alignment by typic

local-aiarxiv-cs-cl

What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations

arXiv:2510.17795v3 Announce Type: replace Abstract: Replicating AI research is a crucial yet challenging task for large language model (LLM) agents. Existing approaches often struggle to generate exec

agentsarxiv-cs-cl

Eco-Bee: A Personalised Multi-Modal Agent for Advancing Student Climate Awareness and Sustainable Behaviour in Campus Ecosystems

arXiv:2604.15327v1 Announce Type: cross Abstract: Universities are microcosms of urban ecosystems, with concentrated consumption patterns in food, transport, energy, and product usage. These environme

20 Apr 2026

LLM attribution analysis across different fine-tuning strategies and model scales for automated code compliance

arXiv:2604.15589v1 Announce Type: cross Abstract: Existing research on large language models (LLMs) for automated code compliance has primarily focused on performance, treating the models as black box

20 Apr 2026

Towards Intrinsic Interpretability of Large Language Models:A Survey of Design Principles and Architectures

arXiv:2604.16042v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have achieved strong performance across many NLP tasks, their opaque internal mechanisms hinder trustworthiness and

safetyarxiv-cs-ai

20 Apr 2026

Can Large Language Models Detect Methodological Flaws? Evidence from Gesture Recognition for UAV-Based Rescue Operation Based on Deep Learning

arXiv:2604.14161v1 Announce Type: new Abstract: Reliable evaluation is essential in machine learning research, yet methodological flaws-particularly data leakage-continue to undermine the validity of

applicationsarxiv-cs-cl

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

Low-Cost System for Automatic Recognition of Driving Pattern in Assessing Interurban Mobility using Geo-Information

arXiv:2604.15216v1 Announce Type: cross Abstract: Mobility in urban and interurban areas, mainly by cars, is a day-to-day activity of many people. However, some of its main drawbacks are traffic jams

Quantitative Approximation Rates for Group Equivariant Learning

arXiv:2602.20370v2 Announce Type: replace Abstract: The universal approximation theorem establishes that neural networks can approximate any continuous function on a compact set. Later works in approx

ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents

arXiv:2604.14261v1 Announce Type: new Abstract: The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-base

Alignment as Institutional Design: From Behavioral Correction to Transaction Structure in Intelligent Systems

arXiv:2604.13079v1 Announce Type: cross Abstract: Current AI alignment paradigms rely on behavioral correction: external supervisors (e.g., RLHF) observe outputs, judge against preferences, and adjust

safetyarxiv-cs-lg

Bridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent Consensus

arXiv:2604.13472v1 Announce Type: new Abstract: Cooperative multi-agent reinforcement learning (MARL) is widely used to address large joint observation and action spaces by decomposing a centralized c

CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation

arXiv:2504.21751v4 Announce Type: replace-cross Abstract: Modern software development demands code that is maintainable, testable, and scalable by organizing the implementation into modular components

Evaluating Supervised Machine Learning Models: Principles, Pitfalls, and Metric Selection

arXiv:2604.13882v1 Announce Type: new Abstract: The evaluation of supervised machine learning models is a critical stage in the development of reliable predictive systems. Despite the widespread avail

Hybrid Approach for Enhancing Lesion Segmentation in Fundus Images

arXiv:2509.25549v2 Announce Type: replace Abstract: Choroidal nevi are common benign pigmented lesions in the eye, with a small risk of transforming into melanoma. Early detection is critical to impro

researcharxiv-cs-cv

Multi-Dimensional Knowledge Profiling with Large-Scale Literature Database and Hierarchical Retrieval

arXiv:2601.15170v2 Announce Type: replace Abstract: The rapid expansion of research across machine learning, vision, and language has produced a volume of publications that is increasingly difficult t

safetyarxiv-cs-cv

The cognitive companion: a lightweight parallel monitoring architecture for detecting and recovering from reasoning degradation in LLM agents

arXiv:2604.13759v1 Announce Type: cross Abstract: Large language model (LLM) agents on multi-step tasks suffer reasoning degradation, looping, drift, stuck states, at rates up to 30% on hard tasks. Cu

Beyond Single-Dimension Novelty: How Combinations of Theory, Method, and Results-based Novelty Shape Scientific Impact

arXiv:2604.12471v1 Announce Type: cross Abstract: Scientific novelty drives advances at the research frontier, yet it is also associated with heightened uncertainty and potential resistance from incum

15 Apr 2026

Calibrated Confidence Estimation for Tabular Question Answering

arXiv:2604.12491v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed for tabular question answering, yet calibration on structured data is largely unstudied. This pap

researcharxiv-cs-cl

15 Apr 2026

Deep Learning using Rectified Linear Units (ReLU)