Search: “evaluation”

Motion Style Slider: Endpoint-Supervised Continuous Style Control for Human Motion Diffusion

arXiv:2609.30795v1 Announce Type: new Abstract: Existing human motion diffusion methods provide strong motion generation quality, and recent style transfer models can inject target style cues, but fin

applicationsarxiv-cs-cv

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Mutable Transcripts: Mitigating Context Pollution through Editable Conversation State

DGX agent

arXiv:2609.31354v1 Announce Type: new Abstract: Contemporary large language model (LLM) chat systems treat conversation history as an immutable sequence of turns that defines the model's working conte

researcharxiv-cs-ai

28 Sept 2026

MVAgent: Multi-Agent Video Generation via Consistent Condition Construction and Shot-Level Policy Optimization

arXiv:2609.30609v1 Announce Type: new Abstract: Multi-shot agentic video generation requires consistent character appearance, stable spatial layout across camera angles, and continuous character state

safetyarxiv-cs-cv

MVVBench: Benchmarking 4D Reasoning in Vision-Language Models

arXiv:2609.30952v1 Announce Type: cross Abstract: Multi-view video understanding requires integrating spatial and temporal evidence across multiple, often non-overlapping camera streams: tracking enti

Neural Parameter Estimation of RC Thermal Building Models for Model Predictive Control

arXiv:2604.05904v2 Announce Type: replace-cross Abstract: Gray-box RC models are widely used to enable energy-efficient model predictive control (MPC) in buildings. However, estimating RC parameters r

NeuralCert: certified computational discovery of extremal mathematical constructions

arXiv:2609.30296v1 Announce Type: new Abstract: Neural networks are becoming popular in solving mathematical problems, but stochastic models do not provide mathematical exactness by themselves. This s

Neuralyzing the Trace: Selective Representation-Level Unlearning with Contrastive Sparse Autoencoders

arXiv:2609.31056v1 Announce Type: new Abstract: Machine unlearning aims to remove targeted information while preserving a model's other abilities. In realistic settings, such as privacy requests under

New LoRA Skills Should Read but Never Write

arXiv:2609.31600v1 Announce Type: new Abstract: Low-rank adapters (LoRA) make it cheap to fine-tune a large language model once per task, but combining several independently trained adapters into one

Not All Memories Are Equal: Hierarchical Collaborative Memory for Validity-Aware Retrieval in LLM Agents

arXiv:2609.30289v1 Announce Type: new Abstract: In team collaboration scenarios, memory is heterogeneous and continually evolving. Team memories capture collective decisions, protocols, and current co

researcharxiv-cs-cl

OC-GS: Gaussian Splatting for Irregular Turntable Capture

arXiv:2609.31572v1 Announce Type: cross Abstract: Uneven rotation and dropped frames make equal-angle assumptions unreliable for turntable reconstruction. We present OC-GS, an object-centric Gaussian

OmouAI: Argumentative Human-AI Policy Deliberation with Simulated Personas

arXiv:2609.31078v1 Announce Type: new Abstract: Debates amongst agents driven by large language models (LLMs) have demonstrated vast potential in various applications, but when these interactions incl

OneWorld: Learning Consistent Physics Across Actions in World Models

arXiv:2609.30946v1 Announce Type: cross Abstract: Action-conditioned video world models aim to predict scene evolution under different actions, a capability that is essential for reliable planning, de

Online Learning via Learned Latent Bayesian Tracking

arXiv:2609.31559v1 Announce Type: new Abstract: Online learning in non-stationary environments requires models to adapt rapidly from streaming data under strict computational constraints. A principled

OpenVAM: Open-World Visual Attention Modeling with VLMs

model-releasesarxiv-cs-cv

arXiv:2609.31364v1 Announce Type: new Abstract: Predicting human gaze is a core capability for applications ranging from web/UI design analysis to robotics and human-computer interaction. Yet, most vi

PALM: Point-in-Time Adaptation for Financial Language Models

model-releasesarxiv-cs-cl

arXiv:2609.30316v1 Announce Type: cross Abstract: Language models used in financial backtests suffer from look-ahead bias, as a model trained on text published after the study period has already obser

Peer-Grounded Counterfactual Path Planning for Chronic Health Management

arXiv:2609.30838v1 Announce Type: new Abstract: Effective behavioral intervention in chronic disease management requires not a single prescription but a sequence of incremental steps, each grounded in

Peer Review as Structured Commentary: Immutable Identity, Public Dialogue, and Reproducible Scholarship

arXiv:2506.22497v2 Announce Type: replace-cross Abstract: This paper reconceptualises peer review as structured public commentary. Traditional academic validation is hindered by anonymity, latency, an

PHASE: Compliance-Enabled Tactile Phase Retrieval for Few-Shot Insertion Learning

arXiv:2609.30889v1 Announce Type: new Abstract: Contact-rich assembly tasks such as peg-in-hole insertion remain difficult to learn from limited demonstrations. While retrieval-augmented imitation lea

safetyarxiv-cs-ro

PICO: Projection-Informed Consistency Optimisation for 6DoF Surgical Tool Pose Estimation

arXiv:2609.30989v1 Announce Type: new Abstract: Purpose: Accurate 6 DoF pose estimation of surgical tools is critical for automa- tion, robotic proprioception, and safe interaction with the tissue ope

PORL: Pretrained Offline Reinforcement Learning for the Job Shop Scheduling Problem

arXiv:2609.30948v1 Announce Type: cross Abstract: The Job Shop Scheduling Problem (JSSP) is a fundamental combinatorial optimization problem in industrial optimization. This work introduces Pretrained

Precision at Speed: Sample-Efficient Online Model-Based Reinforcement Learning for Hydraulic Excavator Control

arXiv:2609.31025v1 Announce Type: cross Abstract: Precise, high-speed control remains challenging for robots with complex actuation dynamics. Learning directly on hardware is further constrained by th

applicationsarxiv-cs-lg

Tutorials

Probabilistic Robustness-driven Universal Adversarial Perturbations with Explainability against Deep Reinforcement Learning-based Intrusion Detection System

arXiv:2609.30605v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) enables adaptive intrusion detection in dynamic network environments but also exposes intrusion detection systems (IDS

tutorialsarxiv-cs-lg

Provable Speech Attributes Conversion via Latent Independence

arXiv:2510.05191v3 Announce Type: replace-cross Abstract: Conditional generation and disentangled representation learning are central to controlled generation across audio, vision, and multimodal doma

applicationsarxiv-cs-ai

Purin: A Biology-inspired Mechanism for Artificial Neural Networks

arXiv:2609.31235v1 Announce Type: new Abstract: Artificial neural networks (ANNs) usually represent neural transmission with fixed trainable weights during a training batch, which omits short-term cha

RAZOR: Pruning Replaceable Experts in LLMs

model-releasesarxiv-cs-cl

arXiv:2609.30465v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models activate few experts per token but store the full expert pool. Expert pruning reduces this storage burden; at a fixed

REALMS: An AI-Assistant Conversational System for Real-Time Exact Audience Sizing over High-Dimensional Nested Profiles

arXiv:2609.30547v1 Announce Type: new Abstract: Audience sizing is a critical component of digital marketing. It enables precise resource allocation, campaign planning, and performance optimization. T

applicationsarxiv-cs-cl

RECAST: From Log Replay to Closed-Loop Driving Simulation with View-Complete Actors

arXiv:2609.31374v1 Announce Type: cross Abstract: Closed-loop driving simulation requires rendered observations to remain reliable as the ego vehicle and surrounding actors move beyond their recorded

Recursive Self-Improvement via On-Policy Distillation for Reasoning

arXiv:2609.30652v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student model by having it generate trajectories, then matching its next-token predictions with an external teache

safetyarxiv-cs-cl

Reinforcement Learning of Communication in a Mesh of Small Language Models

arXiv:2609.30578v1 Announce Type: new Abstract: Language models gain accuracy from more compute at test time, but majority voting over independent samples saturates: as samples grow, the vote converge

safetyarxiv-cs-lg

Reliability-Regulated Trajectory Optimization for Progressive COLMAP-Free 3D Gaussian Splatting

arXiv:2609.30865v1 Announce Type: new Abstract: COLMAP-free 3D Gaussian Splatting (3DGS) bypasses computationally expensive structure-from-motion (SfM) pipelines, yet progressive camera pose tracking

Representation-Guided Generation and Integration of Executable Programs for Robot Manipulation

arXiv:2609.31337v1 Announce Type: new Abstract: Building a robotic manipulation system requires connecting perception, planning, and control through carefully designed representations and interfaces.

applicationsarxiv-cs-ro

Resource-Optimized and Energy-Aware Agentic AI Framework Anchored on Blockchain for Secure Software Supply Chains

arXiv:2609.31282v1 Announce Type: cross Abstract: This paper proposes a blockchain-backed agentic security framework designed to safeguard the complete software development lifecycle (SDLC) while also

Retail Product Search: A Practical Approach at Target

arXiv:2609.31498v1 Announce Type: cross Abstract: Search is one of the most important features in e-commerce, directly driving customer engagement and business growth. A good product search system mus

applicationsarxiv-cs-lg

Agents

Rethinking Data Quality for AI-Driven Systems: Evidence from Practitioner Interviews

arXiv:2609.31191v1 Announce Type: cross Abstract: Data quality research has usually treated data as an input that is stored, processed, and validated. In AI-driven software-intensive systems, data als

agentsarxiv-cs-ai

Scaffold: Support Graph Theory Based Sparsification for Graph Neural Networks

arXiv:2609.31466v1 Announce Type: new Abstract: Graph neural networks (GNNs) rely on message passing over graph edges, making their computational and memory costs strongly dependent on graph density.

Scale-invariant Gaussian derivative residual networks

arXiv:2603.02843v2 Announce Type: replace Abstract: Generalisation across image scales remains a fundamental challenge for deep networks, which often fail to handle images at scales not seen during tr

Scaling Density Functional Theory with Gaussian Splatting

arXiv:2609.31483v1 Announce Type: cross Abstract: Density functional theory (DFT) strikes a practical balance between accuracy and computational cost in many problems of computational chemistry and ma

SEA-CLIP-Tiny: Efficient Multilingual Text-Vision Embedding for Southeast Asian Languages

arXiv:2609.30739v1 Announce Type: new Abstract: Multilingual text-vision embedding models are essential for cross-lingual image-text retrieval, but Southeast Asian languages remain poorly supported du

researcharxiv-cs-cl

Agents

SkillEvoReg: Regularizing Agent Skill Evolution Against Overfitting

arXiv:2609.30861v1 Announce Type: new Abstract: Language-model agents increasingly improve by converting execution experience into reusable external skills. Yet repeated skill updates form a learning

agentsarxiv-cs-ai

SkillFlow: Scalable and Efficient Agent Skill Retrieval System

arXiv:2504.06188v3 Announce Type: replace Abstract: AI agents can extend their capabilities at inference time by loading reusable skills into context, yet equipping an agent with too many skills, part

Tutorials

SoGuDiff: Socially Guided Diffusion for Steerable, Norm-Grounded Robot Navigation

arXiv:2609.30560v1 Announce Type: new Abstract: Beyond collision avoidance, socially competent robot navigation requires adherence to implicit social conventions that vary across contexts, cultures, a

tutorialsarxiv-cs-ro

SPO: Discovering Adaptive Large Neighborhood Search Operators via Stackelberg Program Optimization

arXiv:2609.31179v1 Announce Type: new Abstract: Large neighborhood search (LNS) relies critically on destroy and repair operators, whose effectiveness depends on both adaptation to the evolving LNS st

Stale-Document Poisoning: When Outdated Retrieval Overrides Correct Model Answers

model-releasesarxiv-cs-cl

arXiv:2609.31342v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is often used to address outdated knowledge by providing external evidence. But retrieval helps only when that evid

Stochastic Bilevel Optimization with Heavy-Tailed Noise

arXiv:2509.14952v3 Announce Type: replace Abstract: This paper considers the smooth bilevel optimization in which the lower-level problem is strongly convex and the upper-level problem is possibly non

Structured-Diffuser: Diffusion with Task-Conditioned Structured Priors for Motion Planning

arXiv:2509.25685v3 Announce Type: replace Abstract: We propose Structured-Diffuser, a diffusion planner that embeds task and motion structure directly into the noise model. Unlike standard diffusion-b

researcharxiv-cs-ro

Structured Reasoning Agentic Framework for Interpretable Critical View of Safety Assessment

model-releasesarxiv-cs-cv

arXiv:2609.31524v1 Announce Type: new Abstract: Surgical scene understanding is critical for computer-assisted intervention, yet laparoscopic cholecystectomy remains challenged by the complex anatomy

Subjects, Not Authors: The Authorship Hazard in Agentic Dataspaces

arXiv:2609.30614v1 Announce Type: cross Abstract: Dataspace connectors decide whether a transfer may occur, not what the transferred value contains, tolerable for contracted applications, not for LLM

Symbiotic Architecture for Post-Hoc Audio Extension of Frozen Language Models

arXiv:2609.30784v1 Announce Type: cross Abstract: This paper proposes an architecture for equipping large language models (LLMs) with audio-understanding capabilities without fine-tuning their weights

researcharxiv-cs-cl