Search: “evaluation”

arXiv:2606.04468v1 Announce Type: cross Abstract: Offline multi-objective optimization (Offline MOO) aims to discover novel Pareto-optimal designs based on static datasets without expensive environmen

tutorialsarxiv-cs-ai

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

PE-MHL: Physics-Encoded Modular Hybrid Layers for Scalable Learning of Complex Systems

DGX agent

arXiv:2606.04290v1 Announce Type: new Abstract: Hybrid models that combine physics-based and data-driven components have shown strong potential for achieving accuracy and interpretability in control a

model-releasesarxiv-cs-lg

4 Jun 2026

PersistBench: When Should Long-Term Memories Be Forgotten by LLMs?

arXiv:2602.01146v2 Announce Type: replace Abstract: Conversational assistants are increasingly integrating long-term memory with large language models (LLMs). This persistence of memories, e.g., the u

Physics-Informed Neural Network Modeling of Biodegradable Contaminant Transport through GCL/SL Composite Liners

arXiv:2606.04392v1 Announce Type: cross Abstract: This study develops a two-domain physics-informed neural network framework for contaminant transport through a GCL/SL composite liner system, in which

researcharxiv-cs-cl

POLARIS: Guiding Small Models to Write Long Stories

arXiv:2606.04095v1 Announce Type: cross Abstract: Small open-weight models struggle at long-form creative writing: their generated stories either fall far short of the requested length, or their quali

Agents

Position: Deployed Reinforcement Learning should be Continual

arXiv:2606.04029v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has received increasing attention and adoption in real-world use cases. Most of these systems follow a train-then-fix para

agentsarxiv-cs-ai

Prompt-Level Distillation: A Non-Parametric Alternative to Model Fine-Tuning for Efficient Reasoning

model-releasesarxiv-cs-cl

arXiv:2602.21103v2 Announce Type: replace Abstract: Advanced reasoning typically requires Chain-of-Thought prompting, which is accurate but incurs prohibitive latency and substantial test-time inferen

Proof-Carrying Agent Actions: Model-Agnostic Runtime Governance for Heterogeneous Agent Systems

arXiv:2606.04104v1 Announce Type: cross Abstract: Agent systems execute through runtimes with very different control points: local coding tools, framework SDKs, managed agent platforms, API gateways,

QPredSGG: Hybrid Quantum Predicate Learning for Long-Tailed Scene Graph Generation

arXiv:2606.04689v1 Announce Type: cross Abstract: Scene Graph Generation (SGG) requires relational reasoning over objects and their interactions, but performance is often limited by severe long-tail p

QuBLAST: A Framework for Quantizing Large Language Models with Block-Level Compression Approach and Activation Scaling Strategy

arXiv:2606.04620v1 Announce Type: cross Abstract: LLMs have become the state-of-the-art algorithms for solving NLP tasks. However, they typically come at huge computational and memory costs, thus maki

Local Ai

R-APS: Compositional Reasoning and In-Context Meta-Learning for Constrained Design via Reflective Adversarial Pareto Search

arXiv:2606.04823v1 Announce Type: new Abstract: Large language models (LLMs) are fluent on open-ended tasks, yet in agentic settings, where a system must plan, use tools, and act over extended horizon

local-aiarxiv-cs-ai

Radiomic Feature Selection Using Gradient Loss of Deep Neural Network for Lung Cancer Stage Detection

arXiv:2606.04453v1 Announce Type: new Abstract: Radiomics enables extraction of quantitative imaging biomarkers from medical images and has become an important tool for computer-aided cancer diagnosis

RAVQ-HoloNet: Rate-Adaptive Vector-Quantized Hologram Compression

arXiv:2511.21035v2 Announce Type: replace Abstract: Holography offers significant potential for AR/VR applications. However, its adoption is limited by the high demand for data compression. Existing d

Agents

Real-World Deployment of a 5G-Connected Edge-Controlled Aerial Robot in Industrial Subterranean Mines

arXiv:2606.04818v1 Announce Type: new Abstract: This article presents the first real-world autonomous flight of a 5G-connected aerial robot controlled by an edge-offloaded controller, and aims to brid

agentsarxiv-cs-ro

Reasoning Shift: How Context Silently Shortens LLM Reasoning

arXiv:2604.01161v2 Announce Type: replace Abstract: Large language models (LLMs) exhibiting test-time scaling behavior, such as extended reasoning traces and self-verification, have demonstrated remar

researcharxiv-cs-lg

ReConFuse: Reconstruction-Error Guided Semantic Fusion for AI-Generated Video Detection

arXiv:2606.04706v1 Announce Type: new Abstract: AI-generated videos are becoming increasingly realistic, raising serious concerns about misinformation, content authenticity, and media trust. Reliable

Local Ai

Recover-LoRA for Aggressive Quantization: Reclaiming Accuracy in 2-Bit Language Models via Low-Rank Adaptation with Knowledge Distillation on Synthetic Data

arXiv:2606.04238v1 Announce Type: cross Abstract: Aggressive weight quantization to 2-bit precision offers substantial throughput and memory gains for large language model (LLM) inference, but typical

local-aiarxiv-cs-ai

Reinforcement Learning from Rich Feedback with Distributional DAgger

arXiv:2606.05152v1 Announce Type: cross Abstract: Reasoning models have advanced rapidly, but the dominant reinforcement learning from verifiable rewards (RLVR) recipe remains surprisingly narrow: sam

Revisiting Privacy Amplification by Subsampling in Selective Release DPSGD

arXiv:2606.04384v1 Announce Type: new Abstract: Machine learning's reliance on sensitive data necessitates privacy-preserving techniques like Differentially Private Stochastic Gradient Descent (DPSGD)

researcharxiv-cs-lg

Robust-LLaVA: On the Effectiveness of Large-Scale Robust Image Encoders for Multi-modal Large Language Models

arXiv:2502.01576v2 Announce Type: replace Abstract: Multi-modal Large Language Models (MLLMs) excel in vision-language tasks but remain vulnerable to visual adversarial perturbations that can induce h

safetyarxiv-cs-cv

RSC: Decentralized Rigid Formation Flocking for Large-Scale Swarms via Hybrid Predictive Control and Online Reconfiguration

arXiv:2606.04248v1 Announce Type: new Abstract: Decentralized rigid formation flocking requires a swarm of autonomous agents to maintain a predetermined geometric configuration while moving, relying s

safetyarxiv-cs-ro

Sequential Data Poisoning in LLM Post-Training

arXiv:2606.04929v1 Announce Type: new Abstract: LLM post-training proceeds through multiple stages, e.g., supervised fine-tuning (SFT) followed by reinforcement learning from human feedback (RLHF) or

researcharxiv-cs-lg

SharpNet: Enhancing MLPs to Represent Functions with Controlled Non-differentiability

arXiv:2601.19683v2 Announce Type: replace Abstract: Multi-layer perceptrons (MLPs) are a standard tool for learning and function approximation, but they inherently produce globally smooth outputs. Con

Shifting the Breaking Point of Flow Matching for Multi-Instance Editing

model-releasesarxiv-cs-cv

arXiv:2602.08749v3 Announce Type: replace Abstract: Flow matching models have recently emerged as an efficient alternative to diffusion, especially for text-guided image generation and editing, offeri

Simulate, Reason, Decide: Scientific Reasoning with LLMs for Simulation-Driven Decision Making

arXiv:2606.04505v1 Announce Type: new Abstract: Scientific simulators are increasingly being integrated into LLM-driven systems for high-stakes simulation-driven decision-making. However, existing fra

researcharxiv-cs-ai

Smart Transportation Without Neurons -- Fair Metro Network Expansion with Tabular Reinforcement Learning

arXiv:2606.04167v1 Announce Type: cross Abstract: We tackle the Metro Network Expansion Problem (MNEP), a subset of the Transport Network Design Problem (TNDP), which focuses on expanding metro system

Solving Zebra Puzzles Using Constraint-Guided Multi-Agent Systems

model-releasesarxiv-cs-cl

arXiv:2407.03956v3 Announce Type: replace-cross Abstract: Prior research has enhanced the ability of Large Language Models (LLMs) to solve logic puzzles using techniques such as chain-of-thought promp

Spatial Artifact Coherence Determines Codec Robustness in Patch-Based rPPG

arXiv:2606.04198v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) achieves low heart-rate error on uncompressed benchmarks yet is deployed over compressed video channels in telehealth

Structure-Aware Prediction of PROTAC-Mediated Protein Degradability via Graph Neural Networks

arXiv:2606.04021v1 Announce Type: cross Abstract: Proteolysis-targeting chimeras (PROTACs) can selectively degrade disease-causing proteins, yet predicting which targets are amenable to degradation re

Supportive Token Revealing for Fast Diffusion Language Model Decoding

arXiv:2606.04236v1 Announce Type: cross Abstract: Discrete diffusion language models can generate text efficiently by updating multiple masked positions in parallel, but this parallelism introduces a

researcharxiv-cs-ai

Teaching Robots to Say 'I Don't Know' : SENTINEL for Uncertainty-Aware SLAM

arXiv:2606.04853v1 Announce Type: new Abstract: Low-cost 2D LiDARs lack the intensity channel that higher-end sensors use to diagnose measurement failures, yet they are widely used on educational and

researcharxiv-cs-ro

The Accountability Horizon: An Impossibility Theorem for Governing Human-Agent Collectives

arXiv:2604.07778v2 Announce Type: replace Abstract: Existing accountability frameworks for AI systems, legal, ethical, and regulatory, rest on a shared assumption: for any consequential outcome, at le

Local Ai

The Biomimetic Architecture of Software 4.0

arXiv:2606.04025v1 Announce Type: cross Abstract: Dominant programming paradigms inherit an execution model optimised for a bygone era of a single human mind instructing a local machine, leaving conte

local-aiarxiv-cs-ai

Applications

The Mechanistic Emergence of Symbol Grounding in Language Models

arXiv:2510.13796v3 Announce Type: replace Abstract: Symbol grounding (Harnad, 1990) describes how symbols such as words acquire their meanings by connecting to real-world sensorimotor experiences. Rec

applicationsarxiv-cs-cl

The Saturation Trap and the Subjectivity of Intervention Timing: Why Affect-Based Triggers and LLM Judges Fail to Time Interventions on Autonomous Agents

arXiv:2606.04296v1 Announce Type: new Abstract: As autonomous AI agents move from conversational systems to long-horizon software execution, runtime safety layers that decide when to interrupt an agen

The Variance Brain Foundation Models Forgot: Third-Order Statistics Predict Cognition Where Billion-Parameter Models Fail

arXiv:2606.04010v1 Announce Type: cross Abstract: Brain foundation models (BFMs) are self-supervised Transformers pretrained on fMRI data. We posit that these models should capture each subject's cogn

Think Fast and Far: Long-Horizon Online POMDP Planning via Rapid State Sampling

arXiv:2606.04355v1 Announce Type: new Abstract: Partially Observable Markov Decision Processes (POMDPs) are a general and principled framework for motion planning under uncertainty. Despite tremendous

safetyarxiv-cs-ro

Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks

arXiv:2606.04317v1 Announce Type: cross Abstract: Deep neural networks are increasingly deployed across heterogeneous and partially untrusted environments, where models are distributed through cloud s

Toward Pre-Deployment Assurance for Enterprise AI Agents: Ontology-Grounded Simulation and Trust Certification

arXiv:2606.04037v1 Announce Type: new Abstract: Pre-deployment verification of enterprise artificial intelligence (AI) agents remains a critical gap between large language model (LLM) capability bench

TransTac: Visuo-Tactile Modality Transition via Ultraviolet-Encoded Transparent Elastomers

arXiv:2606.04477v1 Announce Type: new Abstract: Vision-based tactile sensors (VBTS) recover high-resolution contact geometry but typically rely on opaque elastomer layers that prevent visual transpare

safetyarxiv-cs-ro

Tree-Based Formalization of Multi-Agent Complementarity in Human-AI Interactions

arXiv:2606.04779v1 Announce Type: new Abstract: Complementarity is the case in which a human--AI interaction (HAI) outperforms the best prediction benchmark available among its members. Although this

Unifying Model-Free Efficiency and Model-Based Representations via Latent Dynamics

arXiv:2602.12643v2 Announce Type: replace-cross Abstract: We present Unified Latent Dynamics (ULD), a novel reinforcement learning algorithm that unifies the efficiency of model-free methods with the

VAMPS: Visual-Assisted Mathematical Problem Solving Benchmark

arXiv:2606.04244v1 Announce Type: new Abstract: Multimodal large language models are increasingly capable of complex reasoning, yet their performance often degrades when they must externalize a proble

VentAgent: When LLMs Learn to Breathe -- Multi-Objective Arbitration for ARDS Ventilation

arXiv:2606.04632v1 Announce Type: cross Abstract: Mechanical ventilation for Acute Respiratory Distress Syndrome (ARDS) requires balancing competing physiological goals, including oxygenation, lung pr

safetyarxiv-cs-cl

veriFIRE: an Industrial Case Study in Verifying Consistency Properties for a DNN-Based Wildfire Detection System

arXiv:2606.04121v1 Announce Type: cross Abstract: We present our ongoing work on the veriFIRE project: a collaboration between industry and academia, aimed at applying verification to increase the rel

safetyarxiv-cs-lg

We're presenting ParseBench at CVPR 2026! ParseBench is the most comprehensive document understanding benchmark for VLMs. ✅ It contains 2k p…

model-releasesjerry-liu--x

We're presenting ParseBench at CVPR 2026! ParseBench is the most comprehensive document understanding benchmark for VLMs. ✅ It contains 2k pages of real-world enterprise documents ✅ It has comprehensi

What If Prompt Injection Never Left? Exploring Cross-Session Stored Prompt Injection in Agentic Systems

arXiv:2606.04425v1 Announce Type: cross Abstract: Modern agentic systems transform LLMs from session-bounded assistants into stateful systems that persist and evolve shared world state across sessions

When Detectors Forget Forensics: Blocking Semantic Shortcuts for Generalizable AI-Generated Image Detection

arXiv:2603.09242v2 Announce Type: replace Abstract: The growing realism of generative models has blurred the boundary between real and synthetic content, posing significant challenges to reliable AI-g