Search: “evaluation”

BIPPO: Budget-Aware Independent PPO for Energy-Efficient Federated Learning Services

arXiv:2511.08142v2 Announce Type: replace Abstract: Federated Learning (FL) is a promising machine learning solution in large-scale IoT systems, guaranteeing load distribution and privacy. However, FL

safetyarxiv-cs-lg

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Capturing Cardiac Cyclicity through Phase-Equivariant Self-Supervised Learning

DGX agent

arXiv:2608.21147v1 Announce Type: new Abstract: The cyclic structure of physiological processes offers a natural prior for self-supervised representation learning, and the cardiac cycle provides a par

model-releasesarxiv-cs-lg

24 Aug 2026

Causal Modeling of Adverse Pregnancy Outcomes via Adaptive LLM Proposals

arXiv:2608.21079v1 Announce Type: new Abstract: Adverse Pregnancy Outcomes (APOs) such as preterm birth and gestational diabetes can have long-term consequences for both the mother and child, yet an u

Consistency Models for Fast MRI Reconstruction Using Regularization by Denoising

arXiv:2608.20561v1 Announce Type: cross Abstract: Diffusion models (DMs) have emerged as powerful generative priors for MRI reconstruction with promising results. Yet DM-based methods require extensiv

researcharxiv-cs-ai

Coverage-Driven Verification for Safety-by-Design in AI-Based Collision Avoidance Systems

arXiv:2608.20864v1 Announce Type: new Abstract: Artificial Intelligence (AI) offers significant potential for future aviation systems; however, its integration into safety-critical applications requir

Curriculum-Aware Interpolate-then-Refine: Learned Physiological Time-Series Imputation under Realistic Missingness

arXiv:2608.21207v1 Announce Type: cross Abstract: Imputing physiological time series (arterial blood pressure, blood glucose, etc.) is essential for addressing the missingness that pervades clinical d

DAMOS: Learning Distortion-Aware Speech Quality Assessment through Explicit Distortion Localization

arXiv:2608.21176v1 Announce Type: cross Abstract: Automatic speech quality assessment aims to predict Mean Opinion Scores (MOS) consistent with human subjective perception and is essential for evaluat

local-aiarxiv-cs-ai

DAOP: Data-Aware Offloading and Predictive Pre-Calculation for Efficient MoE Inference

arXiv:2501.10375v3 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models, though highly effective for various machine learning tasks, face significant deployment challenges on memory-

local-aiarxiv-cs-lg

Tutorials

Decoupled Vision-Language System for Multimodal Understanding and Generation

arXiv:2608.20382v1 Announce Type: new Abstract: We introduce a new architecture design for multimodal large language models (MLLMs), Libra, capable of both multimodal understanding and generation. Lib

tutorialsarxiv-cs-cl

Degree-Mass Message Passing for Betweenness Ranking in Directed and Undirected Networks

model-releasesarxiv-cs-lg

arXiv:2602.09716v2 Announce Type: replace Abstract: Computing the importance of nodes in networks is a long-standing fundamental problem that has driven extensive study of various centrality measures.

Directional Contextual Representations for Dependency Relations: Why Cross-Direction Pairing Fails

arXiv:2608.20647v1 Announce Type: new Abstract: Splitting a bidirectional LSTM's contextual representation into a forward-only F_i (strictly a function of tokens 1..i) and a backward-only B_i (strictl

researcharxiv-cs-cl

Agents

Don't Solve, Just Compare: Tiny Advisors for Runtime Intervention in LLM Agents

arXiv:2608.21027v1 Announce Type: new Abstract: LLM agents are emerging as an important paradigm for real-world tasks that require reasoning, tool use, and sequential decision-making. As these agents

agentsarxiv-cs-ai

DreamBench-SWE: A Multi-Session Memory-Hygiene Benchmark for Software Agents

arXiv:2608.20664v1 Announce Type: new Abstract: DreamBench-SWE is a multi-session benchmark for software-agent memory hygiene in which later software tasks depend on non-inferable evidence from earlie

EmotionDialogCN: A Spontaneous Multimodal Dataset for Mandarin Emotional Dialogue

arXiv:2608.20905v1 Announce Type: new Abstract: Face-to-face audiovisual interaction is central to human communication, conveying rich emotional and social cues. However, existing multimodal dialogue

safetyarxiv-cs-cv

EndoLIFT: Language-Disambiguated Latent-Conditioned Rectified Flow for Bidirectional Endoscopic Control

arXiv:2608.20478v1 Announce Type: new Abstract: Routine gastrointestinal endoscopy is intrinsically bidirectional: the instrument is advanced to reach target anatomy and later withdrawn or retroflexed

safetyarxiv-cs-ro

EviRank: Structured Relevance Evidence for Multimodal Image Re-ranking

arXiv:2608.20886v1 Announce Type: new Abstract: Real-world image search queries are multimodal and compositional: ``find this shirt in pink'' specifies an entity to retain, an attribute to modify, and

applicationsarxiv-cs-cv

Explaining Intrinsic Moral Self-Correction with Mechanistic Interpretability

arXiv:2505.11924v4 Announce Type: replace-cross Abstract: Intrinsic moral self-correction refers to the phenomenon where a language model refines its ethical judgments or aligns its outputs purely thr

safetyarxiv-cs-ai

Fast Coordinated Bimanual Motion Planning With Hard Constraints

arXiv:2608.20946v1 Announce Type: new Abstract: Bimanual manipulation enables complex tasks but introduces added complexity from the high number of degrees of freedom involved. When handling rigid obj

applicationsarxiv-cs-ro

FlavourBench: Ranking Frontier Language Models with Executable Culinary Ground Truth

arXiv:2608.20574v1 Announce Type: new Abstract: Open-ended language-model benchmarks usually inherit a judge: a human preference panel, another model, or a brittle exact-match key. We introduce Flavou

ForeTime-VLA: Causal Future-Token Distillation from a World Action Model for Conveyor-Belt Manipulation

arXiv:2608.20735v1 Announce Type: new Abstract: Manipulating moving objects requires a policy to anticipate contact events, yet vision-language-action (VLA) policies are commonly fine-tuned from the c

safetyarxiv-cs-ai

From a Static Multi-Level Small Semantic Codebook to a Dynamic Single-Level Large Semantic Codebook for Generative Recommendation

arXiv:2608.21012v1 Announce Type: cross Abstract: Generative recommendation represents each item with a sequence of discrete Semantic IDs (SIDs) and predicts the sequence to retrieve the next item. Ty

Hardware

From Attention Masks to Inert Zero-Vector Tokens: OAttention and O-Closure for Token Dynamics

arXiv:2608.21174v1 Announce Type: new Abstract: Attention masks are relation-level controls: they specify which query--source pairs may interact. They do not provide a representation-carried token sta

hardwarearxiv-cs-ai

GhostTac: Manipulating Tactile Sensors without Physical Contact

arXiv:2608.20817v1 Announce Type: cross Abstract: Tactile sensors are integral to modern robotic systems, enabling robots to perceive and interact with the physical environment through tactile feedbac

researcharxiv-cs-ro

Grounded-Exo2Ego: Structured Semantic Grounding for Robust Exocentric-to-Egocentric Video Generation

arXiv:2608.20534v1 Announce Type: new Abstract: Generating egocentric video from a single exocentric video is an emerging and important topic for AR/VR and physical AI. Compared with conventional nove

researcharxiv-cs-cv

GroupSegment-SHAP: Shapley Value Explanations with Group-Segment Players for Multivariate Time Series

arXiv:2601.06114v2 Announce Type: replace-cross Abstract: Multivariate time-series models achieve strong predictive performance in healthcare, industry, energy, and finance, but how they combine cross

applicationsarxiv-cs-ai

Hadith computational science in the age of large language models: a critical narrative review

arXiv:2608.20364v1 Announce Type: cross Abstract: We examine how hadith computational science is being reshaped by transformer models, retrieval-grounded pipelines, and large language models (LLMs). R

Identity-Preserving Text-to-Video Generation via Agentic Enhancement and Semantic Repair

model-releasesarxiv-cs-cv

arXiv:2608.20749v1 Announce Type: new Abstract: Identity-preserving video generation aims to synthesize videos that follow natural-language instructions while maintaining the visual identity of a give

If It Walks Like an Arbitrage: Protocol-Agnostic Detection with Decidable Structural Equivalence

arXiv:2608.20377v1 Announce Type: cross Abstract: Ethereum transactions admit a canonical structural form. Each execution trace is built into an abstract syntax tree of token transfers grouped by call

Infrared Hotspot-Guided Early Warning of Lithium-Ion Battery Thermal Runaway Under Mechanical Abuse

arXiv:2608.20383v1 Announce Type: cross Abstract: Mechanical abuse can trigger thermal runaway (TR) in lithium-ion batteries through localized heat generation before sensor signals become decisive. Th

local-aiarxiv-cs-ai

Intent Engine: Natural-Language Intent Translation for Intent-Driven Orchestration in the Compute Continuum

model-releasesarxiv-cs-cl

arXiv:2608.20388v1 Announce Type: new Abstract: Microservice placement in the compute continuum is driven by low-level Service-level Objectives (SLOs), but requiring users to specify metric-level cons

InverFill: One-Step Inversion for Enhanced Few-Step Diffusion Inpainting

arXiv:2603.23463v2 Announce Type: replace-cross Abstract: Recent diffusion-based models achieve photorealism in image inpainting but require many sampling steps, limiting practical use. Few-step text-

researcharxiv-cs-ai

Jacobian-guided Noise Injection for Quantization Robustness in Large Language Models

arXiv:2608.20988v1 Announce Type: cross Abstract: Quantization of Large Language Models (LLMs) is often hindered by the sensitivity of the self-attention mechanism to discretization errors. We identif

local-aiarxiv-cs-ai

Keep Your Friends Close, and the Right Neighbours Closer: Disaster-Conditioned Kernel-Regularized Graph Attention for Building Damage Classification

arXiv:2608.20548v1 Announce Type: new Abstract: Disaster damage is spatial: buildings rarely fail in isolation. Yet using spatial context for damage classification remains surprisingly underexplored,

local-aiarxiv-cs-cv

Keyed Provenance Watermarking with Complementary Lattice-Based Secure Aggregation for Federated Learning

arXiv:2608.20580v1 Announce Type: cross Abstract: Federated learning (FL) is vulnerable to multi-level attacks. However, existing methods address them separately, leaving FL exposed to data leakage, u

Knowing but Not Saying: Preventing Factual Access Failures in LLM SFT via Recall-Anchored Distillation

arXiv:2608.20794v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) can degrade factual behavior outside the target domain. This degradation is often described as catastrophic forgetting, yet

Lift, Associate, and Fuse: A Decision-Centric Framework for 2D-to-3D Foundation Model Transfer

arXiv:2608.20659v1 Announce Type: new Abstract: Methods that transfer predictions from two-dimensional foundation models into three-dimensional segmentation are commonly grouped by task or representat

researcharxiv-cs-cv

MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generation

arXiv:2601.06519v2 Announce Type: replace Abstract: Biomedical retrieval-augmented generation (RAG) can ground LLM answers in medical literature, yet long-form outputs often contain isolated unsupport

safetyarxiv-cs-cl

MeltwaterBench: Deep learning for spatiotemporal downscaling of surface meltwater

arXiv:2512.12142v2 Announce Type: replace-cross Abstract: The Greenland ice sheet is melting at an accelerated rate due to processes that are not fully understood and hard to measure. The distribution

MIL-BERT: Classification of Arbitrarily Large Text with Performance and Explanatory Guarantees

arXiv:2608.20636v1 Announce Type: new Abstract: Many text classification decisions are viable based on constituent excerpts alone. Taking inspiration from the field of multiple instance learning, we p

safetyarxiv-cs-cl

Mind the Style: Impact of Communication Style on Human-Chatbot Interaction

arXiv:2602.17850v2 Announce Type: replace-cross Abstract: Conversational agents increasingly mediate everyday digital interactions, yet the effects of their communication style on user experience and

safetyarxiv-cs-ai

Minimax Optimality of Score-Entropy Discrete Diffusion

arXiv:2608.20635v1 Announce Type: cross Abstract: Discrete diffusion models have demonstrated strong performance across a range of datasets, including natural language data and graph-structured data.

researcharxiv-cs-lg

Natural-Language-Guided Generator-Agnostic Shortlisting for Protein Binder Design

arXiv:2608.20755v1 Announce Type: new Abstract: Modern de novo design workflows generate many candidate protein binders, but wet-lab validation capacity remains limited, making shortlisting a major bo

Natural Sit-to-Stand Motion Synthesis For Humanoids via Guided Assistance Curricula and Staged Rewards

arXiv:2608.20823v1 Announce Type: new Abstract: A humanoid has infinitely many ways to stand up from sitting while maintaining balance, making sit-to-stand (STS) a challenging control problem. We synt

safetyarxiv-cs-ro

NeSAM: Neuro-Symbolic Kinodynamics with Soil Adaptation for Off-Road Mobility

arXiv:2608.21330v1 Announce Type: new Abstract: Accurate prediction of off-road vehicle motion over deformable terrain remains challenging because sinkage, slip, and traction vary with local soil cond

local-aiarxiv-cs-ro

NeuroStrata: An Electroencephalographic Connectivity-Aware Deep Representation Learning Framework for Dynamic Brain Network Analysis of Mental Stress

arXiv:2608.20354v1 Announce Type: cross Abstract: This study introduces NeuroStrata, a connectivity-aware deep representation learning framework for EEG-based mental stress analysis using Time-Varying

researcharxiv-cs-ai

Nothing Changed but the Model: CellFill -- Bounded In-Cell Learning for Bit-Identical, Revocable Updates to Quantized LLMs

model-releasesarxiv-cs-lg

arXiv:2608.20873v1 Announce Type: new Abstract: Every way of teaching a deployed language model something new -- full fine-tuning, adapter merging, model editing -- replaces the released checkpoint, a

One LLM wrote a trading feature. Another reviewed it. Both missed a future-data bug

An AQuA research loop let one LLM write an intraday trading feature and a second LLM review it for causality. The feature divided the volume seen so far by the day's final total volume. At prediction

local-air-localllama

Agents

Peer-Voted LLM-Agent Stress Tests Find Feed-Induced Lexical Convergence but No Reliable Matched-Exposure Advantage for Distributed Sources

arXiv:2608.20438v1 Announce Type: cross Abstract: Population-level behavior in large-language-model (LLM) agents cannot be characterized by single-agent benchmarks. We introduce PV-SST, a peer-voted s

agentsarxiv-cs-ai