Search: “framework”

A Systematic Evaluation of Molecular Mixture Behavior Prediction

arXiv:2605.29698v1 Announce Type: new Abstract: Machine learning for molecular property prediction has focused largely on pure compounds, even though many practical applications depend on mixtures wit

researcharxiv-cs-lg

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AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning

DGX agent

arXiv:2602.23258v2 Announce Type: replace Abstract: While Multi-Agent Systems (MAS) excel in complex reasoning, they suffer from the cascading impact of erroneous information from individual agents. C

model-releasesarxiv-cs-ai

29 May 2026

An End-to-End PyTorch Interface for Differentiable PDE Solvers: A RANS Model-Correction Study

model-releasesarxiv-cs-lg

arXiv:2605.28858v1 Announce Type: cross Abstract: This work presents an end-to-end strategy for solving inverse problems constrained by Partial Differential Equations within a fully differentiable Mac

Assessing Dutch Syllabification Algorithms and Improving Accuracy by Combining Phonetic and Orthographic Information through Deep Learning

arXiv:2605.28834v1 Announce Type: cross Abstract: Syllabification describes the task of dividing words into syllables. Due to many rules and exceptions, training an algorithm to perform syllabificatio

AutoSizer: Automatic Sizing of Analog and Mixed-Signal Circuits via Large Language Model (LLM) Agents

arXiv:2602.02849v2 Announce Type: replace Abstract: The design of Analog and Mixed-Signal (AMS) integrated circuits remains heavily reliant on expert knowledge, with transistor sizing a major bottlene

Hardware

Bastion: Budget-Aware Speculative Decoding with Tree-structured Block Diffusion Drafting

arXiv:2605.29727v1 Announce Type: new Abstract: Block-diffusion drafters have recently emerged as a powerful alternative for speculative decoding by predicting multiple future-token distributions in a

hardwarearxiv-cs-lg

Battery-Sim-Agent: Leveraging LLM-Agent for Inverse Battery Parameter Estimation

arXiv:2605.29560v1 Announce Type: new Abstract: Parameterizing high-fidelity 'digital twins' of batteries is a critical yet challenging inverse problem that hinders the pace of battery innovation. Pre

Local Ai

Benchmarking at the Edge of Comprehension

arXiv:2602.14307v3 Announce Type: replace Abstract: As frontier Large Language Models (LLMs) increasingly saturate new benchmarks shortly after they are published, benchmarking itself is at a juncture

local-aiarxiv-cs-ai

Brain-IT-VQA: From Brain Signals to Answers

arXiv:2605.29588v1 Announce Type: cross Abstract: Decoding visual content from fMRI signals recorded while a person views images, and specifically answering questions about the seen images, is a long-

Bridge-RAG: An Abstract Bridge Tree Based Retrieval Augmented Generation Algorithm

arXiv:2603.26668v2 Announce Type: replace-cross Abstract: As an important paradigm for enhancing the generation quality of Large Language Models (LLMs), retrieval-augmented generation (RAG) faces the

CalArena: A Large-Scale Post-Hoc Calibration Benchmark

arXiv:2605.30188v1 Announce Type: cross Abstract: Reliable probability estimates are critical in many machine learning applications, yet modern classifiers are often poorly calibrated. Post-hoc calibr

Calibration Is Not Enough: Evaluating Confidence Estimation Under Language Variations

arXiv:2601.08064v2 Announce Type: replace Abstract: Confidence estimation (CE) indicates how reliable the answers of large language models are and impacts user trust and decision-making. Existing eval

safetyarxiv-cs-cl

City-Mesh3R: Simulation-Ready City-Scale 3D Mesh Reconstruction from Multi-View Images

arXiv:2605.30310v1 Announce Type: cross Abstract: City-scale 3D surface reconstruction from multiview images for downstream 3D simulation, poses highly challenging problems due to the scale and comple

CogniVerse: Revolutionizing Multi-Modal Retrieval-Augmented Generation with Cognitive Reflection and Geometric Reasoning

arXiv:2605.29602v1 Announce Type: new Abstract: Multi-modal Retrieval-Augmented Generation (MMRAG) has emerged as a powerful paradigm for enhancing Multimodal Large Language Models in knowledge-intens

researcharxiv-cs-cv

Colored Noise Diffusion Sampling

arXiv:2605.30332v1 Announce Type: new Abstract: Diffusion models achieve state-of-the-art image synthesis, with their generative trajectories fundamentally exhibiting a spectral bias, resolving low-fr

safetyarxiv-cs-cv

COMET: Concept Space Dissection of the Modality Gap in Audio-Text Multimodal Contrastive Embeddings

arXiv:2605.29628v1 Announce Type: cross Abstract: Contrastive Language-Audio Pretraining (CLAP) models are widely used for audio understanding and support modality-agnostic condition swapping in many

CRITIC-R1: Learning Structured Critics for Retrieval-Augmented Generation

arXiv:2605.29886v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves knowledge-intensive question answering by incorporating external evidence. However, existing RAG methods

DefSynUS: Real-time Patient-specific Intrahepatic Vessel Identification via Deformation-Aware CT-US Domain Adaptation

arXiv:2605.29570v1 Announce Type: new Abstract: Purpose: Laparoscopic ultrasound (LUS) enhances the safety of liver surgery by visualizing intrahepatic vessels in real-time. Still, vessel identificati

safetyarxiv-cs-cv

ElegantVLA: Learning When to Think for Efficient Vision-Language-Action Models

arXiv:2605.29438v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are a powerful paradigm for generalist robotic control. However, their high computational cost and limited control f

tutorialsarxiv-cs-ro

Agents

Error as a Lens: Probing LLM Reasoning through Synthetic Misconception Generation

arXiv:2605.29007v1 Announce Type: new Abstract: Personalized tutoring, teacher training, and education research need access to targeted synthetic misconceptions, but privacy and IRB constraints make l

agentsarxiv-cs-cl

EVADE: LLM-Based Explanation Generation and Validation for Error Detection in NLI

arXiv:2511.08949v2 Announce Type: replace Abstract: High-quality datasets are critical for training and evaluating reliable NLP models. In tasks like natural language inference (NLI), human label vari

researcharxiv-cs-cl

Evaluating Dataset Watermarking for Fine-tuning Traceability of Customized Diffusion Models: A Comprehensive Benchmark and Removal Approach

arXiv:2511.19316v2 Announce Type: replace-cross Abstract: Recent fine-tuning techniques for diffusion models enable them to reproduce specific image sets, such as particular faces or artistic styles,

Evolutionary Refinement of Generative Graph Topologies: A Hybrid WGAN-GA Approach

arXiv:2605.29161v1 Announce Type: cross Abstract: Generating realistic graph-structured data is challenging due to discrete connectivity, varying graph sizes, and class-specific structural patterns. R

EvoMD-LLM: Learning the Language of Species Evolution in Reactive Molecular Dynamics

arXiv:2605.29394v1 Announce Type: new Abstract: While large language models (LLMs) excel at static scientific reasoning, they struggle to model the temporal structure of dynamic physical processes. We

EvoRubric: Self-Evolving Rubric-Driven RL for Open-Ended Generation

arXiv:2605.29847v1 Announce Type: new Abstract: Reinforcement Learning (RL) has significantly advanced Large Language Models (LLMs) in verifiable domains, but aligning models for open-ended generation

safetyarxiv-cs-cl

Financially Guided Deep Portfolio Optimization

arXiv:2605.28853v1 Announce Type: cross Abstract: Portfolio optimization in real-world financial markets is notoriously difficult due to non-stationarity, noisy data, and high transaction costs. Stand

tutorialsarxiv-cs-lg

Genetically Aligned Patient Representations Improve Hematological Diagnosis

arXiv:2605.29980v1 Announce Type: cross Abstract: Multimodal alignment of histopathology encoders with transcriptomic and genomic data has been shown to significantly improve performance in downstream

HiKEY: Hierarchical Multimodal Retrieval for Open-Domain Document Question Answering

arXiv:2605.29606v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) for document-based Open-domain Question Answering (ODQA) on large-scale industrial corpora faces two critical bottl

Hista and Numca: Estimate State Value Effectively for LLM Reinforcement Learning

arXiv:2605.29782v1 Announce Type: cross Abstract: Reinforcement learning (RL) refines large language models (LLMs) by directly optimizing model behavior through reward signals. While accurate state va

In-Context Reward Adaptation for Robust Preference Modeling

arXiv:2605.30323v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback (RLHF) typically relies on static reward models to align Large Language Models with human preferences. Howe

Kernel-based potential mean-field games with unbiased random Fourier U-statistics

model-releasesarxiv-cs-lg

arXiv:2605.29371v1 Announce Type: cross Abstract: We study the subclass of potential mean-field games in which the running interaction cost and the terminal target cost are both expressed through repr

Learnable Assessment Skills for LLM-based Automated Scoring: Rubric Construction via Iterative Optimization

arXiv:2605.29274v1 Announce Type: new Abstract: LLM-based automated scoring approaches near-human performance, but scaling to new tasks remains bottlenecked by the per-item human configuration of upst

tutorialsarxiv-cs-cl

Learning Robust and Task-Invariant Functional Representation from fMRI through Siamese Self-Supervised Learning

arXiv:2605.28990v1 Announce Type: new Abstract: Functional magnetic resonance imaging (fMRI) is a powerful tool for investigating human brain function. However, the high cost of data acquisition and t

tutorialsarxiv-cs-lg

Learning to Feel Materials from Multisensory Tactile Data via Interpretable Models

arXiv:2605.29572v1 Announce Type: new Abstract: Human tactile perception of materials relies on complex multisensory touch cues, yet the relationship between low-level tactile signals and perceptual r

tutorialsarxiv-cs-ro

Less Is More: Elevating RAG via Performance-Driven Context Compression

arXiv:2508.19282v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a promising paradigm for improving the timeliness of knowledge updates and the factual acc

LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation

arXiv:2605.29280v1 Announce Type: cross Abstract: Knowledge distillation (KD) transfers a single scalar prediction from a large foundation model (FM) to compact vertical models (VMs), suffering from d

Mesh-Aware Epipolar Matching for Multi-View Multi-Person 3D Pose Estimation in Basketball

arXiv:2605.29953v1 Announce Type: new Abstract: Multi-view multi-person 3D pose estimation in team sports scenarios remains challenging due to player occlusions, appearance similarity caused by team u

researcharxiv-cs-cv

Neural Operator-Based Surrogate Model for CFD:Helical Coil Steam Generator in Small Modular Reactor

arXiv:2605.30277v1 Announce Type: new Abstract: Real-time thermal-hydraulic simulation is essential for digital twin (DT) technology that supports the safe and efficient operation of small modular rea

safetyarxiv-cs-lg

OmniCustom: Sync Audio-Video Customization Via Joint Audio-Video Generation Model

arXiv:2602.12304v4 Announce Type: replace-cross Abstract: Existing mainstream video customization methods focus on generating identity-consistent videos based on given reference images and textual pro

Paper Agents, Paper Gains: An Empirical Analysis of DeFi Investment Agents

arXiv:2605.29174v1 Announce Type: new Abstract: DeFi investment agents, systems that use AI for autonomous on-chain trading, have attained over USD 3 billion in combined token valuations since late 20

PersonaAgent: Bridging Memory and Action for Personalized LLM Agents

arXiv:2506.06254v2 Announce Type: replace Abstract: Large Language Model (LLM) empowered agents have recently emerged as advanced paradigms that exhibit impressive capabilities in a wide range of doma

PRAIB: Peer Review AI Benchmark of Behaviour of LLM-Assisted Reviewing

arXiv:2605.29815v1 Announce Type: new Abstract: The growing number of submitted papers has motivated the exploration of Large Language Models (LLMs) as a means to support and augment the peer review p

Predicting Causal Effects from Natural Language Queries using Structured Representations

arXiv:2605.29631v1 Announce Type: cross Abstract: Randomized controlled trials are a cornerstone of medicine and the social sciences as they enable reliable estimates of causal effects. However, they

Probabilistic bias adjustment of seasonal forecasts using generative machine learning: A case study of Arctic sea ice predictions

model-releasesarxiv-cs-lg

arXiv:2605.29172v1 Announce Type: new Abstract: Seasonal climate predictions support planning and risk management by offering early information of the most likely-to-occur climate conditions in the co

Provably Secure Agent Guardrail

arXiv:2605.29251v1 Announce Type: new Abstract: As large language models transition from bounded generative engines to agents with expansive execution privileges, AI going out of control precipitates

Reasoning While Asking: Transforming Reasoning Large Language Models from Passive Solvers to Proactive Inquirers

arXiv:2601.22139v2 Announce Type: replace-cross Abstract: Reasoning-oriented Large Language Models (LLMs) have achieved remarkable progress with Chain-of-Thought (CoT) prompting, yet they remain funda

Relevance as a Vulnerability: How Web Retrieval Degrades Safety Alignment in LLM Agents

arXiv:2605.29224v1 Announce Type: cross Abstract: AI agents augment large language models with external tools such as web retrieval, enabling grounded and up-to-date responses. However, incorporating

Riemannian AmbientFlow: Towards Simultaneous Manifold Learning and Generative Modeling from Corrupted Data

arXiv:2601.18728v2 Announce Type: replace Abstract: Modern generative modeling methods have demonstrated strong performance in learning complex data distributions from clean samples. In many scientifi

researcharxiv-cs-lg