Search: “benchmark”

ASTRA: Enhancing Multi-Subject Generation with Retrieval-Augmented Pose Guidance and Disentangled Position Embedding

arXiv:2604.13938v1 Announce Type: new Abstract: Subject-driven image generation has shown great success in creating personalized content, but its capabilities are largely confined to single subjects i

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Model Releases

Beyond Uniform Sampling: Synergistic Active Learning and Input Denoising for Robust Neural Operators

DGX agent

arXiv:2604.13316v1 Announce Type: new Abstract: Neural operators have emerged as fast surrogate models for physics simulations, yet they remain acutely vulnerable to adversarial perturbations, a criti

model-releasesarxiv-cs-lg

16 Apr 2026

Local Ai

BioTrain: Sub-MB, Sub-50mW On-Device Fine-Tuning for Edge-AI on Biosignals

arXiv:2604.13359v1 Announce Type: new Abstract: Biosignals exhibit substantial cross-subject and cross-session variability, inducing severe domain shifts that degrade post-deployment performance for s

local-aiarxiv-cs-lg

BOAT: Navigating the Sea of In Silico Predictors for Antibody Design via Multi-Objective Bayesian Optimization

arXiv:2604.13980v1 Announce Type: new Abstract: Antibody lead optimization is inherently a multi-objective challenge in drug discovery. Achieving a balance between different drug-like properties is cr

Breaking the Generator Barrier: Disentangled Representation for Generalizable AI-Text Detection

arXiv:2604.13692v1 Announce Type: new Abstract: As large language models (LLMs) generate text that increasingly resembles human writing, the subtle cues that distinguish AI-generated content from huma

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

C-voting: Confidence-Based Test-Time Voting without Explicit Energy Functions

arXiv:2604.13521v1 Announce Type: new Abstract: Neural network models with latent recurrent processing, where identical layers are recursively applied to the latent state, have gained attention as pro

C^2T: Captioning-Structure and LLM-Aligned Common-Sense Reward Learning for Traffic--Vehicle Coordination

arXiv:2604.13098v1 Announce Type: cross Abstract: State-of-the-art (SOTA) urban traffic control increasingly employs Multi-Agent Reinforcement Learning (MARL) to coordinate Traffic Light Controllers (

Caption First, VQA Second: Knowledge Density, Not Task Format, Drives Multimodal Scaling

arXiv:2604.13054v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved rapid progress, yet their scaling behavior remains less clearly characterized and often less pred

researcharxiv-cs-cl

Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning

arXiv:2604.13504v1 Announce Type: cross Abstract: Designing effective reward functions is a cornerstone of reinforcement learning (RL), yet it remains a challenging and labor-intensive process due to

ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding

arXiv:2603.27064v2 Announce Type: replace-cross Abstract: Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a ca

safetyarxiv-cs-cl

Tutorials

Coding agents learn from experience, but that knowledge stays locked in silos. Solve a thousand SWE tasks, and none of that wisdom helps wit…

Coding agents learn from experience, but that knowledge stays locked in silos. Solve a thousand SWE tasks, and none of that wisdom helps with competitive coding. What if memories could transfer across

tutorialsdair-ai--x

Concrete Jungle: Towards Concreteness Paved Contrastive Negative Mining for Compositional Understanding

arXiv:2604.13313v1 Announce Type: new Abstract: Vision-Language Models demonstrate remarkable capabilities but often struggle with compositional reasoning, exhibiting vulnerabilities regarding word or

Counterfactual Peptide Editing for Causal TCR--pMHC Binding Inference

arXiv:2604.13256v1 Announce Type: new Abstract: Neural models for TCR-pMHC binding prediction are susceptible to shortcut learning: they exploit spurious correlations in training data -- such as pepti

Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions

arXiv:2405.19088v3 Announce Type: replace Abstract: Recent advancements in large multimodal language models have demonstrated remarkable proficiency across a wide range of tasks. Yet, these models sti

Debate to Align: Reliable Entity Alignment through Two-Stage Multi-Agent Debate

arXiv:2604.13551v1 Announce Type: new Abstract: Entity alignment (EA) aims to identify entities referring to the same real-world object across different knowledge graphs (KGs). Recent approaches based

safetyarxiv-cs-cl

Decoding the Delta: Unifying Remote Sensing Change Detection and Understanding with Multimodal Large Language Models

arXiv:2604.14044v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general vision-language tasks, their application to remote sensing change understanding is hinde

Design Space Exploration of Hybrid Quantum Neural Networks for Chronic Kidney Disease

arXiv:2604.13608v1 Announce Type: new Abstract: Hybrid Quantum Neural Networks (HQNNs) have recently emerged as a promising paradigm for near-term quantum machine learning. However, their practical pe

Doc-V*:Coarse-to-Fine Interactive Visual Reasoning for Multi-Page Document VQA

arXiv:2604.13731v1 Announce Type: new Abstract: Multi-page Document Visual Question Answering requires reasoning over semantics, layouts, and visual elements in long, visually dense documents. Existin

safetyarxiv-cs-cl

DRG-Font: Dynamic Reference-Guided Few-shot Font Generation via Contrastive Style-Content Disentanglement

arXiv:2604.13797v1 Announce Type: new Abstract: Few-shot Font Generation aims to generate stylistically consistent glyphs from a few reference glyphs. However, capturing complex font styles from a few

Drowsiness-Aware Adaptive Autonomous Braking System based on Deep Reinforcement Learning for Enhanced Road Safety

arXiv:2604.13878v1 Announce Type: new Abstract: Driver drowsiness significantly impairs the ability to accurately judge safe braking distances and is estimated to contribute to 10%-20% of road acciden

Dual-Enhancement Product Bundling: Bridging Interactive Graph and Large Language Model

arXiv:2604.14030v1 Announce Type: new Abstract: Product bundling boosts e-commerce revenue by recommending complementary item combinations. However, existing methods face two critical challenges: (1)

researcharxiv-cs-cl

Echoes Over Time: Unlocking Length Generalization in Video-to-Audio Generation Models

arXiv:2602.20981v3 Announce Type: replace Abstract: Scaling multimodal alignment between video and audio is challenging, particularly due to limited data and the mismatch between text descriptions and

EmbodiedClaw: Conversational Workflow Execution for Embodied AI Development

model-releasesarxiv-cs-ro

arXiv:2604.13800v1 Announce Type: new Abstract: Embodied AI research is increasingly moving beyond single-task, single-environment policy learning toward multi-task, multi-scene, and multi-model setti

EMGFlow: Robust and Efficient Surface Electromyography Synthesis via Flow Matching

arXiv:2604.13685v1 Announce Type: cross Abstract: Deep learning-based surface electromyography (sEMG) gesture recognition is frequently bottlenecked by data scarcity and limited subject diversity. Whi

Enhanced Text-to-Image Generation by Fine-grained Multimodal Reasoning

arXiv:2604.13491v1 Announce Type: new Abstract: With the rapid progress of Multimodal Large Language Models (MLLMs), unified MLLMs that jointly perform image understanding and generation have advanced

Enhancing Confidence Estimation in Telco LLMs via Twin-Pass CoT-Ensembling

arXiv:2604.13271v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly applied to complex telecommunications tasks, including 3GPP specification analysis and O-RAN network troub

Enhancing Mixture-of-Experts Specialization via Cluster-Aware Upcycling

arXiv:2604.13508v1 Announce Type: new Abstract: Sparse Upcycling provides an efficient way to initialize a Mixture-of-Experts (MoE) model from pretrained dense weights instead of training from scratch

ESCAPE: Episodic Spatial Memory and Adaptive Execution Policy for Long-Horizon Mobile Manipulation

arXiv:2604.13633v1 Announce Type: new Abstract: Coordinating navigation and manipulation with robust performance is essential for embodied AI in complex indoor environments. However, as tasks extend o

Evaluating LLM-Based Translation of a Low-Resource Technical Language: The Medical and Philosophical Greek of Galen

arXiv:2602.24119v2 Announce Type: replace Abstract: Purpose: This study evaluates the quality of commercial large language model (LLM) machine translation (MT) for Ancient Greek technical prose and be

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

Exposia: Teaching and Assessment of Academic Writing Skills for Research Project Proposals and Peer Feedback

arXiv:2601.06536v2 Announce Type: replace Abstract: We present Exposia, the first public dataset that connects writing and feedback in higher education, enabling research on educationally grounded com

ExpSeek: Self-Triggered Experience Seeking for Web Agents

arXiv:2601.08605v2 Announce Type: replace Abstract: Experience intervention in web agents emerges as a promising technical paradigm, enhancing agent interaction capabilities by providing valuable insi

Failure Makes the Agent Stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions

arXiv:2509.18847v3 Announce Type: replace-cross Abstract: Tool-augmented large language models (LLMs) are usually trained with supervised imitation or coarse-grained reinforcement learning that optimi

FAST: A Synergistic Framework of Attention and State-space Models for Spatiotemporal Traffic Prediction

arXiv:2604.13453v1 Announce Type: new Abstract: Traffic forecasting requires modeling complex temporal dynamics and long-range spatial dependencies over large sensor networks. Existing methods typical

Applications

Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective

arXiv:2604.14025v1 Announce Type: new Abstract: Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and i

applicationsarxiv-cs-cv

FiLM-Nav: Efficient and Generalizable Navigation via VLM Fine-tuning

model-releasesarxiv-cs-ro

arXiv:2509.16445v2 Announce Type: replace Abstract: Enabling robotic assistants to navigate complex environments and locate objects described in free-form language is a critical capability for real-wo

Flow-based Generative Modeling of Potential Outcomes and Counterfactuals

arXiv:2505.16051v4 Announce Type: replace-cross Abstract: Predicting potential and counterfactual outcomes from observational data is central to individualized decision-making, particularly in clinica

fMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding

arXiv:2511.21760v3 Announce Type: replace Abstract: Recent advances in multimodal large language models (LLMs) have enabled unified reasoning across images, audio, and video, but extending such capabi

Free Geometry: Refining 3D Reconstruction from Longer Versions of Itself

arXiv:2604.14048v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models are efficient but rigid: once trained, they perform inference in a zero-shot manner and cannot adapt to the test s

Local Ai

From Anchors to Supervision: Memory-Graph Guided Corpus-Free Unlearning for Large Language Models

arXiv:2604.13777v1 Announce Type: new Abstract: Large language models (LLMs) may memorize sensitive or copyrighted content, raising significant privacy and legal concerns. While machine unlearning has

local-aiarxiv-cs-cl

From Prediction to Justification: Aligning Sentiment Reasoning with Human Rationale via Reinforcement Learning

arXiv:2604.13398v1 Announce Type: new Abstract: While Aspect-based Sentiment Analysis (ABSA) systems have achieved high accuracy in identifying sentiment polarities, they often operate as 'black boxes

researcharxiv-cs-cl

From Synchrony to Sequence: Exo-to-Ego Generation via Interpolation

arXiv:2604.13793v1 Announce Type: new Abstract: Exo-to-Ego video generation aims to synthesize a first-person video from a synchronized third-person view and corresponding camera poses. While paired s

Local Ai

GeoLink: A 3D-Aware Framework Towards Better Generalization in Cross-View Geo-Localization

arXiv:2604.13183v1 Announce Type: new Abstract: Generalizable cross-view geo-localization aims to match the same location across views in unseen regions and conditions without GPS supervision. Its cor

local-aiarxiv-cs-cv

Geometric Context Transformer for Streaming 3D Reconstruction

arXiv:2604.14141v1 Announce Type: new Abstract: Streaming 3D reconstruction aims to recover 3D information, such as camera poses and point clouds, from a video stream, which necessitates geometric acc

Graph Propagated Projection Unlearning: A Unified Framework for Vision and Audio Discriminative Models

arXiv:2604.13127v1 Announce Type: new Abstract: The need to selectively and efficiently erase learned information from deep neural networks is becoming increasingly important for privacy, regulatory c

Tools

Great to be at HumanX with @Silverside_AI @LumaLabsAI and @krea_ai The SF frontier AI builder community keeps getting stronger. We're not do…

Great to be at HumanX with @Silverside_AI @LumaLabsAI and @krea_ai The SF frontier AI builder community keeps getting stronger. We're not done yet. Keep track of when and where you can meet up with th

toolsfireworks-ai--x

HAMLET: Switch your Vision-Language-Action Model into a History-Aware Policy

arXiv:2510.00695v3 Announce Type: replace-cross Abstract: Inherently, robotic manipulation tasks are history-dependent: leveraging past context could be beneficial. However, most existing Vision-Langu