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Energy Scaling Laws for Diffusion Models: Quantifying Compute in Image Generation

arXiv:2511.17031v2 Announce Type: replace-cross Abstract: The rapidly growing computational demands of diffusion models for image generation have raised significant concerns about energy consumption a

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Human DGX agent

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Research

ENSEMBITS: an alphabet of protein conformational ensembles

DGX agent

arXiv:2605.13789v1 Announce Type: cross Abstract: Protein structure tokenizers (PSTs) are workhorses in protein language modeling, function prediction, and evolutionary analysis. However, existing PST

researcharxiv-cs-ai

14 May 2026

Entropy Aware Reward Guidance for Diffusion Language Model Alignment

arXiv:2602.05000v2 Announce Type: replace-cross Abstract: Reward guidance, also known as posterior sampling, is a popular method for test-time adaptation and post-training in continuous diffusion mode

Ergodic Trajectory Design by Learned Pushforward Maps: Provable Coverage via Conditional Flow Matching

arXiv:2605.13063v1 Announce Type: new Abstract: Designing continuous trajectories whose time-averaged occupancy provably matches a prescribed spatial density (the ergodic coverage problem) is central

ERPPO: Entropy Regularization-based Proximal Policy Optimization

arXiv:2605.13131v1 Announce Type: new Abstract: Multi-Agent Proximal Policy Optimization (MAPPO) is a variant of the Proximal Policy Optimization (PPO) algorithm, specifically tailored for multi-agent

EVA-Bench: A New End-to-end Framework for Evaluating Voice Agents

arXiv:2605.13841v1 Announce Type: cross Abstract: Voice agents, artificial intelligence systems that conduct spoken conversations to complete tasks, are increasingly deployed across enterprise applica

Applications

EvObj: Learning Evolving Object-centric Representations for 3D Instance Segmentation without Scene Supervision

arXiv:2605.13152v1 Announce Type: cross Abstract: We introduce EvObj for unsupervised 3D instance segmentation that bridges the geometric domain gap between synthetic pretraining data and real-world p

applicationsarxiv-cs-ai

Tutorials

EvoGround: Self-Evolving Video Agents for Video Temporal Grounding

arXiv:2605.13803v1 Announce Type: new Abstract: Video temporal grounding (VTG) takes an untrimmed video and a natural-language query as input and localizes the temporal moment that best matches the qu

tutorialsarxiv-cs-cv

Exact Sequence Interpolation with Transformers

arXiv:2502.02270v3 Announce Type: replace Abstract: We prove that transformers can exactly interpolate datasets of finite input sequences in R^d, dgeq 2, with corresponding output sequences of smaller

Applications

Exact Verification of Graph Neural Networks with Incremental Constraint Solving

arXiv:2508.09320v3 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) are increasingly often employed in high-stakes applications, such as fraud detection or healthcare, but are susce

applicationsarxiv-cs-ai

Exemplar-Free Continual Learning for State Space Models

arXiv:2505.18604v3 Announce Type: replace Abstract: State-Space Models (SSMs) excel at capturing long-range dependencies with structured recurrence, making them well-suited for sequence modeling. Howe

Explaining and Breaking the Safety-Helpfulness Ceiling via Preference Dimensional Expansion

arXiv:2605.11679v2 Announce Type: replace Abstract: In the realm of multi-objective alignment for large language models, balancing disparate human preferences often manifests as a zero-sum conflict. S

Exploring how EFL students talk to and through AI to develop texts

arXiv:2605.12523v1 Announce Type: cross Abstract: Generative Artificial Intelligence (AI) introduces new considerations for English as a foreign language (EFL) writing pedagogy. This study explores ho

Exploring Human-Robot Collaboration: Analysis of Interaction Modalities in Challenging Tasks

arXiv:2605.13380v1 Announce Type: new Abstract: This work compares three interaction modalities for human-robot collaboration: passive, reactive, and proactive. We studied 18 participants assembling a

researcharxiv-cs-ro

Exploring Multimodal LMMs for Online Episodic Memory Question Answering on the Edge

arXiv:2602.22455v2 Announce Type: replace Abstract: We investigate the feasibility of using Multimodal Large Language Models (MLLMs) for real-time online episodic memory question answering. While clou

Exploring the holographic entropy cone via reinforcement learning

arXiv:2601.19979v2 Announce Type: replace-cross Abstract: We develop a reinforcement learning algorithm to study the holographic entropy cone. Given a target entropy vector, our algorithm searches for

Exponential Approximation Rates and Parameter Efficiency of Learnable Bernstein Activations

arXiv:2602.04264v2 Announce Type: replace-cross Abstract: The choice of activation function fundamentally shapes the representational capacity and parameter efficiency of deep neural networks, yet mos

F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking

arXiv:2605.12995v1 Announce Type: new Abstract: Traditional retrieval pipelines optimize utility through stages of candidate retrieval and reranking, where ranking operates over a predefined candidate

Fast and Compact Graph Cuts for the Boykov-Kolmogorov Algorithm

arXiv:2605.13402v1 Announce Type: new Abstract: Computing a minimum s-t cut in a graph is a solution to a wide range of computer vision problems, and is often done using the Boykov-Kolmogorov (BK) alg

Fast and effective algorithms for fair clustering at scale

arXiv:2605.13759v1 Announce Type: new Abstract: Clustering is an unsupervised machine learning task that consists of identifying groups of similar objects. It has numerous applications and is increasi

Local Ai

FeatCal: Feature Calibration for Post-Merging Models

arXiv:2605.13030v1 Announce Type: cross Abstract: Model merging combines task experts into one model and avoids joint training, retraining, or deploying many expert models, but the merged model often

local-aiarxiv-cs-ai

Feature Learning Dynamics in Infinite-Depth Neural Networks

arXiv:2512.21075v2 Announce Type: replace-cross Abstract: Deep neural networks have achieved remarkable success in practice, yet a mechanistic understanding of how features evolve during training rema

FedHPro: Federated Hyper-Prototype Learning via Gradient Matching

arXiv:2605.13475v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative training of distributed clients while protecting privacy. To enhance generalization capability in FL, prot

FePySR: A Neural Feature Extraction Framework for Efficient and Scalable Symbolic Regression

arXiv:2605.12704v1 Announce Type: cross Abstract: A fundamental challenge in symbolic regression (SR) is efficiently recovering complex mathematical expressions from observational data. Although this

Few-shot Multi-Task Learning of Linear Invariant Features with Meta Subspace Pursuit

arXiv:2409.02708v2 Announce Type: replace Abstract: Data scarcity poses a serious threat to modern machine learning and artificial intelligence, as their practical success typically relies on the avai

Few-Shot Physics-Informed Neural Network for Shape Reconstruction of Concentric-Tube Robots

model-releasesarxiv-cs-ro

arXiv:2605.12790v1 Announce Type: new Abstract: Modeling concentric tube robots (CTRs) involves complex nonlinear continuum mechanics, and despite recent progress, physics-based models often lack an a

Agents

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition

arXiv:2605.13193v1 Announce Type: new Abstract: Fine-grained recognition in everyday life is often not a closed-book classification problem: when encountering unfamiliar objects, humans actively searc

agentsarxiv-cs-cv

Filter-then-Weight: Online Data Selection and Reweighting for LLM Fine-Tuning

arXiv:2604.00001v2 Announce Type: replace-cross Abstract: Gradient-based data selection offers a principled framework for estimating sample utility in large language model (LLM) fine-tuning, but exist

Agents

Finding the Weakest Link: Adversarial Attack against Multi-Agent Communications

arXiv:2605.13170v1 Announce Type: new Abstract: Multi-agent systems rely on communication for information sharing and action coordination, which exposes a vulnerability to attacks. We investigate sing

agentsarxiv-cs-lg

Hardware

FlashSampling: Fast and Memory-Efficient Exact Sampling

arXiv:2603.15854v2 Announce Type: replace-cross Abstract: Sampling from a categorical distribution is mathematically simple, but in large-vocabulary decoding, it often triggers extra memory traffic an

hardwarearxiv-cs-ai

Hardware

Flow Augmentation and Knowledge Distillation for Lightweight Face Presentation Attack Detection

arXiv:2605.13108v1 Announce Type: new Abstract: Face presentation attack detection (FacePAD) remains challenging under diverse spoofing representation, including 2D print and replay, 3D mask-based spo

hardwarearxiv-cs-cv

Flow Matching for Offline Reinforcement Learning with Discrete Actions

arXiv:2602.06138v2 Announce Type: replace Abstract: Generative policies based on diffusion models and flow matching have shown strong promise for offline reinforcement learning (RL), but their applica

Flow Matching with Uncertainty Quantification and Guidance

arXiv:2602.10326v2 Announce Type: replace Abstract: Despite the remarkable success of sampling-based generative models such as flow matching, they can still produce samples of inconsistent or degraded

researcharxiv-cs-cv

Applications

FMC-DETR: Frequency-Decoupled Multi-Domain Coordination for Aerial-View Object Detection

arXiv:2509.23056v2 Announce Type: replace Abstract: Remote sensing object detection is a critical technology for real-world applications such as natural resource monitoring, traffic management, and UA

applicationsarxiv-cs-cv

FOAM: Blocked State Folding for Memory-Efficient LLM Training

arXiv:2512.07112v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated remarkable performance due to their large parameter counts and extensive training data. However

Follow-Bench: A Unified Motion Planning Benchmark for Socially-Aware Robot Person Following

model-releasesarxiv-cs-ro

arXiv:2509.10796v4 Announce Type: replace Abstract: Robot person following (RPF) -- mobile robots that follow and assist a specific person -- has emerging applications in personal assistance, security

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs

arXiv:2605.13788v1 Announce Type: new Abstract: Active learning for machine-learning interatomic potentials (MLIPs) must address several challenges to be practical: scaling to large candidate pools, l

Formal Conjectures: An Open and Evolving Benchmark for Verified Discovery in Mathematics

arXiv:2605.13171v1 Announce Type: new Abstract: As automated reasoning systems advance rapidly, there is a growing need for research-level formal mathematical problems to accurately evaluate their cap

FRAME: Forensic Routing and Adaptive Multi-path Evidence Fusion for Image Manipulation Detection

arXiv:2605.12826v1 Announce Type: cross Abstract: The proliferation of sophisticated image editing tools and generative artificial intelligence models has made verifying the authenticity of digital im

FrameSkip: Learning from Fewer but More Informative Frames in VLA Training

arXiv:2605.13757v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are commonly trained from dense robot demonstration trajectories, often collected through teleoperation, by sampli

safetyarxiv-cs-ro

Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation

arXiv:2605.12997v1 Announce Type: new Abstract: Neural operators learn to map initial conditions to the terminal solution of partial differential equations (PDEs), providing a surrogate for the full o

From Baselines to Transport Geodesics: Axiomatic Attribution via Optimal Generative Flows

arXiv:2603.05093v2 Announce Type: replace-cross Abstract: Feature attributions often hide a critical modeling choice: they explain a prediction along a counterfactual path from a reference state to an

From Generalist to Specialist Representation

arXiv:2605.12733v1 Announce Type: cross Abstract: Given a generalist model, learning a task-relevant specialist representation is fundamental for downstream applications. Identifiability, the asymptot

From Heuristics to Analytics: Forecasting Effort and Progress in Online Learning

arXiv:2605.12788v1 Announce Type: new Abstract: Sustained effort is essential for realizing the benefits of intelligent tutoring systems (ITS), yet many learners disengage or underuse available practi

From Instance Selection to Fixed-Pool Data Recipe Search for Supervised Fine-Tuning

arXiv:2605.12944v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) data selection is commonly formulated as instance ranking: score each example and retain a top-k subset. However, effective

From Pixels to BFS: High Maze Accuracy Does Not Imply Visual Planning

arXiv:2603.26839v2 Announce Type: replace-cross Abstract: How do multimodal models solve visual spatial tasks -- through genuine planning, or through brute-force search in token space? We introduce ex

GAAMA: Graph Augmented Associative Memory for Agents

arXiv:2603.27910v2 Announce Type: replace Abstract: AI agents that interact with users across multiple sessions require persistent long-term memory to maintain coherent, personalized behavior. Current

GAGPO: Generalized Advantage Grouped Policy Optimization

arXiv:2605.13217v1 Announce Type: cross Abstract: Reinforcement learning has become a powerful paradigm for post-training large language model agents, yet credit assignment in multi-turn environments