Search: “research”

Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values

arXiv:2605.10365v1 Announce Type: new Abstract: Autonomous agents have rapidly matured as task executors and seen widespread deployment via harnesses such as OpenClaw. Safety concerns have rightly dra

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Model Releases

Alice v1: Distillation-Enhanced Video Generation Surpassing Closed-Source Models

DGX agent

arXiv:2605.08115v1 Announce Type: cross Abstract: Wepresent Alice v1, a 14-billion parameter open-source video generation model that achieves state-of-the-art quality through consistency distillation

model-releasesarxiv-cs-cv

12 May 2026

AtteConDA: Attention-Based Conflict Suppression in Multi-Condition Diffusion Models and Synthetic Data Augmentation

arXiv:2605.09425v1 Announce Type: cross Abstract: Recent conditional image generation methods can improve controllability by generating images that are faithful to conditions such as sketches, human p

agentsarxiv-cs-ai

Tutorials

Attention-based graph neural networks: a survey

arXiv:2605.08679v1 Announce Type: cross Abstract: Graph neural networks (GNNs) aim to learn well-trained representations in a lower-dimension space for downstream tasks while preserving the topologica

tutorialsarxiv-cs-ai

Balancing Efficiency and Fairness in Traffic Light Control through Deep Reinforcement Learning

arXiv:2605.10170v1 Announce Type: new Abstract: Urban traffic congestion presents a significant challenge for modern cities, which impacts mobility and sustainability. Traditional traffic light contro

safetyarxiv-cs-lg

BenchHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognition

model-releasesarxiv-cs-cv

arXiv:2605.08296v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from wearable sensors supports broad healthcare and behavior science applications. However, data heterogeneity and the

Tutorials

CauSim: Scaling Causal Reasoning with Increasingly Complex Causal Simulators

arXiv:2605.09079v1 Announce Type: new Abstract: Despite surpassing human performance across mathematics, coding, and other knowledge-intensive tasks, large language models (LLMs) continue to struggle

tutorialsarxiv-cs-ai

CellDX AI Autopilot: Agent-Guided Training and Deployment of Pathology Classifiers

arXiv:2605.10362v1 Announce Type: new Abstract: Training AI models for computational pathology currently requires access to expensive whole-slide-image datasets, GPU infrastructure, deep expertise in

hardwarearxiv-cs-cv

ChartDiff: A Large-Scale Benchmark for Comprehending Pairs of Charts

arXiv:2603.28902v2 Announce Type: replace Abstract: Charts are central to analytical reasoning, yet existing benchmarks for chart understanding focus almost exclusively on single-chart interpretation

Computer Use at the Edge of the Statistical Precipice

arXiv:2605.08261v1 Announce Type: cross Abstract: Evaluating Computer Use Agents (CUAs) on interactive environments is fraught with methodological pitfalls that the field has yet to systematically add

ConFit v3: Improving Resume-Job Matching with LLM-based Re-Ranking

arXiv:2605.09760v1 Announce Type: new Abstract: A reliable resume-job matching system helps a company find suitable candidates from a pool of resumes and helps a job seeker find relevant jobs from a l

Coordinates of Capability: A Unified MTMM-Geometric Framework for LLM Evaluation

arXiv:2605.08522v1 Announce Type: new Abstract: The evaluation of Large Language Models (LLMs) faces a critical challenge in construct validity, where fragmented benchmarks and ad hoc metrics frequent

EAR: Enhancing Uni-Modal Representations for Weakly Supervised Audio-Visual Video Parsing

arXiv:2605.08723v1 Announce Type: new Abstract: Weakly supervised Audio-Visual Video Parsing (AVVP) aims to recognize and temporally localize audio, visual, and audio-visual events in videos using onl

local-aiarxiv-cs-cv

Efficient Evaluation of LLM Performance with Statistical Guarantees

arXiv:2601.20251v3 Announce Type: replace-cross Abstract: Exhaustively evaluating many large language models (LLMs) on a large suite of benchmarks is expensive. We cast benchmarking as finite-populati

End-to-End Keyword Spotting on FPGA Using Graph Neural Networks with a Neuromorphic Auditory Sensor

arXiv:2605.09570v1 Announce Type: new Abstract: With the rapid growth of mobile robotics and embedded intelligence, there is an increasing demand for efficient on-device data processing on edge platfo

local-aiarxiv-cs-lg

Energy Consumption of Dataframe Libraries for End-to-End Deep Learning Pipelines:A Comparative Analysis

arXiv:2511.08644v3 Announce Type: replace-cross Abstract: This paper presents a detailed comparative analysis of the performance of three major Python data manipulation libraries - Pandas, Polars, and

hardwarearxiv-cs-ai

Engineering Robustness into Personal Agents with the AI Workflow Store

arXiv:2605.10907v1 Announce Type: cross Abstract: The dominant paradigm for AI agents is an 'on-the-fly' loop in which agents synthesize plans and execute actions within seconds or minutes in response

agentsarxiv-cs-ai

EpiGraph: A Knowledge Graph and Benchmark for Evidence-Intensive Reasoning in Epilepsy

arXiv:2605.09505v1 Announce Type: new Abstract: Epilepsy diagnosis and treatment require evidence-intensive reasoning across heterogeneous clinical knowledge, including biosignal patterns, genetic mec

Evolutionary Ensemble of Agents

arXiv:2605.09018v1 Announce Type: cross Abstract: We introduce Evolutionary Ensemble (EvE), a decentralized framework that organizes existing, highly capable coding agents into a live, co-evolving sys

agentsarxiv-cs-ai

Applications

Explainable Machine Learning Framework for Cardiovascular Disease Diagnosis and Prognosis

arXiv:2507.11185v2 Announce Type: replace-cross Abstract: Heart disease continues to pose a critical worldwide health issue, more specifically in areas with insufficient access to healthcare infrastru

applicationsarxiv-cs-ai

FairHealth: An Open-Source Python Library for Trustworthy Healthcare AI in Low-Resource Settings

arXiv:2605.08198v1 Announce Type: cross Abstract: We present FairHealth, an open-source Python library that provides a unified, modular framework for trustworthy machine learning in healthcare applica

Fairness vs Performance: Characterizing the Pareto Frontier of Algorithmic Decision Systems

arXiv:2605.10604v1 Announce Type: cross Abstract: Designing fair algorithmic decision systems requires balancing model performance with fairness toward affected individuals: More fairness might requir

Applications

Forecasting Source Stability in Scientific Experiments using Temporal Learning Models: A Case Study from Tritium Monitoring

arXiv:2605.08140v1 Announce Type: cross Abstract: The Karlsruhe Tritium Neutrino Experiment (KATRIN) aims to measure the absolute neutrino mass with unprecedented sensitivity, requiring precise monito

applicationsarxiv-cs-ai

FormalRewardBench: A Benchmark for Formal Theorem Proving Reward Models

arXiv:2605.10141v1 Announce Type: new Abstract: Recent neural theorem provers use reinforcement learning with verifiable rewards (RLVR), where proof assistants provide binary correctness signals. Whil

From Traditional Taggers to LLMs: A Comparative Study of POS Tagging for Medieval Romance Languages

arXiv:2605.09147v1 Announce Type: cross Abstract: Part-of-speech (POS) tagging for Medieval Romance languages remains challenging due to orthographic variation, morphological complexity, and limited a

General Agent Evaluation

arXiv:2602.22953v2 Announce Type: replace Abstract: General-purpose agents perform tasks in unfamiliar environments without domain-specific manual customization. Yet no study has systematically measur

GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction

arXiv:2605.09973v1 Announce Type: cross Abstract: Reliable detection of personally identifiable information (PII) is increasingly important across modern data-processing systems, yet the task remains

Governing AI-Assisted Security Operations: A Design Science Framework for Operational Decision Support

arXiv:2605.09534v1 Announce Type: cross Abstract: Engineering managers increasingly must decide how to introduce generative artificial intelligence (AI), retrieval-augmented generation, and coding age

GraphBench: Next-generation graph learning benchmarking

arXiv:2512.04475v5 Announce Type: replace-cross Abstract: Machine learning on graphs has made substantial progress across domains such as molecular property prediction and chip design. Yet benchmarkin

GravityGraphSAGE: Link Prediction in Directed Attributed Graphs

arXiv:2605.09408v1 Announce Type: new Abstract: Link prediction (inferring missing or future connections between nodes in a graph) is a fundamental problem in network science with widespread applicati

Higher Resolution, Better Generalization: Unlocking Visual Scaling in Deep Reinforcement Learning

arXiv:2605.10546v1 Announce Type: new Abstract: Pixel-based deep reinforcement learning agents are typically trained on heavily downsampled visual observations, a convention inherited from early bench

Incremental Multilingual Text2Cypher with Adapter Combination

arXiv:2601.16097v2 Announce Type: replace Abstract: Large Language Models enable users to access database using natural language interfaces using tools like Text2SQL, Text2SPARQL, and Text2Cypher, whi

Large Language Models over Networks: Collaborative Intelligence under Resource Constraints

arXiv:2605.08626v1 Announce Type: cross Abstract: Large language models (LLMs) are transforming society, powering applications from smartphone assistants to autonomous driving. Yet cloud-based LLM ser

local-aiarxiv-cs-lg

Leveraging LLMs to Automate Energy-Aware Refactoring of Parallel Scientific Codes

arXiv:2505.02184v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used for generating parallel scientific codes, with a primary focus on generating functionally correct

hardwarearxiv-cs-ai

LLaVA-UHD v4: What Makes Efficient Visual Encoding in MLLMs?

model-releasesarxiv-cs-cv

arXiv:2605.08985v1 Announce Type: new Abstract: Visual encoding constitutes a major computational bottleneck in Multimodal Large Language Models (MLLMs), especially for high-resolution image inputs. T

Tutorials

LLM-Augmented Chemical Synthesis and Design Decision Programs

arXiv:2505.07027v2 Announce Type: replace Abstract: Retrosynthesis, the process of breaking down a target molecule into simpler precursors through a series of valid reactions, stands at the core of or

tutorialsarxiv-cs-ai

LLMs for Secure Hardware Design and Related Problems: Opportunities and Challenges

arXiv:2605.10807v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into Electronic Design Automation (EDA) and hardware security is rapidly reshaping the semiconductor i

hardwarearxiv-cs-lg

LLMSYS-HPOBench: Hyperparameter Optimization Benchmark Suite for Real-World LLM Systems

arXiv:2605.08305v1 Announce Type: cross Abstract: Large Language Model (LLM) systems have been the frontier of AI in many application domains, leading to new challenges and opportunities for hyperpara

Locking Pretrained Weights via Deep Low-Rank Residual Distillation

arXiv:2605.10777v1 Announce Type: new Abstract: The quality of open-weight language models has dramatically improved in recent years. Sharing weights greatly facilitates model adoption by enabling the

Magis-Bench: Evaluating LLMs on Magistrate-Level Legal Tasks

arXiv:2605.08437v1 Announce Type: cross Abstract: Existing benchmarks for legal AI focus primarily on tasks where LLMs must produce legal arguments or documents, yet the capacity to judge such argumen

MapNav: A Novel Memory Representation via Annotated Semantic Maps for Vision-and-Language Navigation

arXiv:2502.13451v5 Announce Type: replace Abstract: Vision-and-language navigation (VLN) is a key task in Embodied AI, requiring agents to navigate diverse and unseen environments while following natu

agentsarxiv-cs-ro

MemQ: Integrating Q-Learning into Self-Evolving Memory Agents over Provenance DAGs

arXiv:2605.08374v1 Announce Type: new Abstract: Episodic memory allows LLM agents to accumulate and retrieve experience, but current methods treat each memory independently, i.e., evaluating retrieval

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image

arXiv:2605.10616v1 Announce Type: cross Abstract: Tabular Foundation Models have recently established the state of the art in supervised tabular learning, by leveraging pretraining to learn generaliza

Multi-domain Multi-modal Document Classification Benchmark with a Multi-level Taxonomy

arXiv:2605.10550v1 Announce Type: new Abstract: Document classification forms the backbone of modern enterprise content management, yet existing benchmarks remain trapped in oversimplified paradigms -

Navigating LLM Valley: From AdamW to Memory-Efficient and Matrix-Based Optimizers

arXiv:2605.09176v1 Announce Type: cross Abstract: Training large language models requires optimization algorithms that are not only statistically effective, but also computationally and memory efficie

On Distinguishing Capability Elicitation from Capability Creation in Post-Training: A Free-Energy Perspective

arXiv:2605.08368v1 Announce Type: new Abstract: Debates about large language model post-training often treat supervised fine-tuning (SFT) as imitation and reinforcement learning (RL) as discovery. But

local-aiarxiv-cs-ai

OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecasting

arXiv:2502.06830v5 Announce Type: replace-cross Abstract: Probabilistic intraday electricity price forecasting is becoming increasingly important for short-term power-system operation. With increasing

Overcoming Catastrophic Forgetting in Visual Continual Learning with Reinforcement Fine-Tuning

arXiv:2605.09640v1 Announce Type: new Abstract: Recent studies suggest that Reinforcement Fine-Tuning (RFT) is inherently more resilient to catastrophic forgetting than Supervised Fine-Tuning (SFT). H

safetyarxiv-cs-cv