Search: “evaluation”

DAST: A VLM-LLM Framework for Cross-Interface Anomaly Detection in O-RAN

arXiv:2606.06261v1 Announce Type: cross Abstract: O-RAN enables a disaggregated baseband stack with programmable functions that communicate over standardized open interfaces. The same openness that en

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Design a Reliable LLM-Integrated Interface for Mortality Forecasting

DGX agent

arXiv:2606.06235v1 Announce Type: cross Abstract: Mortality forecasting plays an important role in actuarial and policy decision-making, but its implementation remains technically complex and inaccess

local-aiarxiv-cs-ai

6 Jun 2026

Double Preconditioning (DoPr): Optimization for Test-Time Performance, not Validation Loss

arXiv:2606.06418v1 Announce Type: cross Abstract: Many modern applications of deep learning involve training a neural network via a one-step prediction loss (e.g., L^2 regression, cross-entropy), but

Edit-R2: Context-Aware Reinforcement Learning for Multi-Turn Image Editing

arXiv:2606.05950v1 Announce Type: new Abstract: Text-guided image editing has advanced rapidly with diffusion models and unified multimodal foundation models. However, most existing methods remain con

Escaping the Verifier: Learning to Reason via Demonstrations

arXiv:2511.21667v4 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) to reason often relies on Reinforcement Learning (RL) with task-specific verifiers. However, many real-w

Finite Element-Based Material Learning via Automatic Differentiation: Learning constitutive neural network models from full-field deformation data

arXiv:2606.05199v1 Announce Type: cross Abstract: The identification of constitutive neural network models from heterogeneous full-field deformation data provides a robust alternative to traditional c

GenTI: Benchmarking LLMs for Autonomous IDPS Rule Generation for Unseen Attacks

arXiv:2606.05844v1 Announce Type: cross Abstract: Rule-based Intrusion Detection and Prevention Systems (IDPS) offer precise attack detection as well as mitigation, however their manually crafted, sig

GITCO: Gated Inference-Time Context Optimization in TSFMs

arXiv:2606.05332v1 Announce Type: new Abstract: Patch-based Time Series Foundation Models (TSFMs) suffer from context poisoning: structurally anomalous patches capture disproportionate attention and s

How Far Did They Go? The Persuasive Tactics of Covert LLM Agents in a Discontinued Field Experiment

arXiv:2606.05256v1 Announce Type: new Abstract: This study analyzes a publicly released dataset from a discontinued field experiment on Reddit's r/ChangeMyView. The intervention, conducted by unknown,

Tutorials

In-Training Defenses against Emergent Misalignment in Language Models

arXiv:2508.06249v3 Announce Type: replace-cross Abstract: Fine-tuning lets practitioners repurpose aligned large language models (LLMs) for new domains, yet recent work reveals emergent misalignment (

tutorialsarxiv-cs-ai

Individual Gain, Collective Loss: Metacognitive Adaptation in AI-Assisted Creativity

arXiv:2606.05532v1 Announce Type: new Abstract: Recent studies reveal a paradox: AI enhances individual creative outputs while reducing collective diversity. Current explanations -- cognitive offloadi

Insurance of Agentic AI

arXiv:2606.05449v1 Announce Type: new Abstract: Agentic artificial intelligence (AI) systems are transforming the risk landscape by extending beyond information generation to autonomous planning, tool

ITP-STDP: An Intrinsic-Timing Power-of-Two Learning Engine for On-Chip SNN Training

arXiv:2606.06159v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) have the potential to emerge as the third generation of neural networks and have attracted increasing attention across

LatentWave: JEPA Pretraining for Wireless Foundation Models

arXiv:2606.06373v1 Announce Type: cross Abstract: Wireless foundation models have emerged as a promising alternative to building separate models for each wireless task. However, existing approaches re

Learning Adaptive Parallel Execution for Efficient Code Localization

arXiv:2601.19568v2 Announce Type: replace Abstract: Code localization constitutes a key bottleneck in automated software development pipelines. While concurrent tool execution can enhance discovery sp

Learning What Matters: Probabilistic Task Selection via Mutual Information for Model Finetuning

arXiv:2507.12612v3 Announce Type: replace-cross Abstract: Supervised fine-tuning performance for large language models depends strongly on how training budget is distributed across a heterogeneous set

Hardware

LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels

arXiv:2603.19312v3 Announce Type: replace-cross Abstract: Joint Embedding Predictive Architectures (JEPAs) offer a compelling framework for learning world models in compact latent spaces, yet existing

hardwarearxiv-cs-ai

LLM Research Papers: The 2026 List (January to May)

researchsebastian-raschka

This resource compiles significant large language model research papers published between January and May 2026, curated by Sebastian Raschka. It serves as a reference guide for tracking recent advance

LLMCodec: Adapting Video Codecs for Efficient Weight Compression of Large Language Models

arXiv:2606.05861v1 Announce Type: cross Abstract: The rapid development of large language models(LLMs) has led to remarkable advances in natural language processing. However, the increasing scale of t

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows

arXiv:2605.12376v2 Announce Type: replace Abstract: Table processing-including cleaning, transformation, augmentation, and matching-is a foundational yet error-prone stage in real-world data pipelines

QCFuse: Query-Aware Cache Fusion via Compressed View for Efficient RAG Serving

arXiv:2606.05875v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves large language model (LLM) answer quality by grounding generation in external evidence, but processing ret

RAINO: Anchoring Agents in Reality, A Systematic Review and Conceptual Framework for Realism in Agent-Based Modelling

arXiv:2606.05167v1 Announce Type: cross Abstract: Realism is a central yet seemingly under-theorized concept in Agent-Based Modelling. This paper presents a Systematic Literature Review, aiming to ide

Reformulating Neural Operators in d+1 Dimensions for Embedding Evolution

arXiv:2505.11766v4 Announce Type: replace-cross Abstract: Neural Operators (NOs) are powerful architectures for learning mappings between function spaces. While most advances focus on refining kernel

Representation Learning Enables Scalable Multitask Deep Reinforcement Learning

arXiv:2606.05555v1 Announce Type: cross Abstract: Scaling reinforcement learning (RL) to diverse multitask settings remains a central challenge. While recent advances in model-based RL achieve strong

Residual Modeling for High-Fidelity Learned Compression of Scientific Data

arXiv:2606.05389v1 Announce Type: new Abstract: Lossy compression is essential for massive spatiotemporal data from scientific simulations. Learned compressors can achieve high compression ratios at m

Applications

Rethinking Infrastructure Inspection as Image Difference Classification: A Traffic Sign Case Study

arXiv:2606.06375v1 Announce Type: new Abstract: Digital twins (DTs) allow the digitalization of road infrastructure inspection, though this is hindered by limited annotated data. This work exploits th

applicationsarxiv-cs-ai

Risk Assessment of Autonomous Driving: Integrating Technical Failures, Ethical Dilemmas, and Policy Frameworks

arXiv:2606.06396v1 Announce Type: new Abstract: Autonomous driving technology has the potential to reduce the large number of road traffic accidents caused by human error each year, but it also brings

Selective-Advantage Entropy-Adaptive Horizon GRPO: Asymmetric Token-Level Discounting for Efficient Reinforcement Learning of Language Models

arXiv:2606.05434v1 Announce Type: cross Abstract: Group Relative Policy Optimisation (GRPO) has emerged as an effective reinforcement-learning algorithm for aligning language models on reasoning tasks

Self-Commitment Latency: A Reward-Free Probe for Prompted Implicit Hacking

arXiv:2606.05625v1 Announce Type: new Abstract: Implicit reward hacking is hard to audit when a language model's chain of thought appears benign: a final answer may be anchored by a prompt shortcut wh

SlotGCG: Exploiting the Positional Vulnerability in LLMs for Jailbreak Attacks

arXiv:2606.05609v1 Announce Type: cross Abstract: As large language models (LLMs) are widely deployed, identifying their vulnerability through jailbreak attacks becomes increasingly critical. Optimiza

Synthetic Contrastive Reasoning for Multi-Table Q&A

arXiv:2606.05382v1 Announce Type: new Abstract: Multi-table question answering requires models to retrieve relevant evidence, link schemas, and perform compositional reasoning across relational tables

The Virtual Roundtable: Multi-Agent Personas Simulating the Dynamics of Human Brainstorming

arXiv:2606.05178v1 Announce Type: cross Abstract: As AI-driven product development accelerates, the bottleneck is shifting from how we build to what we build. Traditional human brainstorming faces cha

Towards AI epidemiology: a measurement standardisation framework for prospective risk detection

arXiv:2512.15783v3 Announce Type: replace Abstract: This paper proposes a measurement standardisation framework that compresses expert-AI interactions into structured, comparable fields for prospectiv

Towards Healthy Evolution: Exploring the Role and Mechanisms of Human-Agent Interaction in Self-Evolving Systems

arXiv:2606.06114v1 Announce Type: new Abstract: Self-evolving agents improve through continual self-play and self-generated learning signals, but autonomous evolution can also cause capability degrada

Towards World Models in Biomedical Research

arXiv:2606.05925v1 Announce Type: new Abstract: A central goal of biomedicine is to understand, predict and ultimately control the dynamic mechanisms by which biological systems respond to perturbatio

Tutorials

TRACE: A Temporal Conditional Estimation for Multimodal Time Series Foundation Models

arXiv:2606.06285v1 Announce Type: new Abstract: Time series foundation models (TS-FMs) aim to learn generalizable temporal representations that can be adapted to a wide range of downstream tasks. In r

tutorialsarxiv-cs-ai

Applications

Uncertainty Aware Functional Behavior Prediction and Material Fatigue Assessment for Circular Factory

arXiv:2606.05334v1 Announce Type: new Abstract: Returned products in circular factories re-enter production with heterogeneous degradation states, usage histories, and remaining capability. Reuse cann

applicationsarxiv-cs-ai

Willing but Unable: Separating Refusal from Capability in Code LLMs via Abliteration

arXiv:2606.05396v1 Announce Type: cross Abstract: Producing a labeled vulnerable code at scale is a recurring obstacle for learning-based vulnerability detection: mined corpora carry substantial label

Local Ai

A Conversational Framework for Human-Robot Collaborative Manipulation with Distributed Generative AI models

arXiv:2606.06061v1 Announce Type: new Abstract: This paper presents a distributed conversational framework for human-robot collaborative manipulation that integrates local language and vision-language

local-aiarxiv-cs-ro

Active Video Perception: Iterative Evidence Seeking for Agentic Long Video Understanding

arXiv:2512.05774v2 Announce Type: replace-cross Abstract: Long video understanding (LVU) is challenging because answering real-world queries often depends on sparse, temporally dispersed cues buried i

agentsarxiv-cs-cl

Adaptive Tokenisation Via Temporal Redundancy Masking And Latent Inpainting

model-releasesarxiv-cs-cv

arXiv:2606.06158v1 Announce Type: new Abstract: Adaptive video tokenisation seeks to dynamically allocate token budgets based on the underlying visual complexity of a sequence. Current continuous-regi

ArcANE: Do Role-Playing Language Agents Stay in Character at the Right Time?

model-releasesarxiv-cs-cl

arXiv:2606.05553v1 Announce Type: new Abstract: Role-playing language agents (RPLAs) should play characters whose values and behavior evolve as the story progresses, not maintain a fixed persona. Exis

Ask or Assume? Uncertainty-Aware Clarification-Seeking in Coding Agents

arXiv:2603.26233v2 Announce Type: replace Abstract: As Large Language Model (LLM) agents are increasingly deployed in open-ended domains like software engineering, they frequently encounter underspeci

agentsarxiv-cs-cl

Applications

Ask-to-Clarify: Resolving Instruction Ambiguity through Multi-turn Dialogue

arXiv:2509.15061v2 Announce Type: cross Abstract: The ultimate goal of embodied agents is to create collaborators that can interact with humans, not mere executors that passively follow instructions.

applicationsarxiv-cs-cv

Attitude-Aided Linear Calibration of Triaxial Accelerometers

arXiv:2606.06308v1 Announce Type: new Abstract: Triaxial MEMS accelerometers are widely used for inertial sensing, navigation, and sensor fusion, but existing calibration methods often rely on costly

safetyarxiv-cs-ro

Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA Models

arXiv:2602.12628v4 Announce Type: replace Abstract: Simulation offers a scalable and low-cost way to enrich vision-language-action (VLA) training, reducing reliance on expensive real-robot demonstrati

safetyarxiv-cs-ro

Breaking Time: A Fully Gaussian Framework for Distributed and Continuous-Time SLAM

model-releasesarxiv-cs-ro

arXiv:2606.06250v1 Announce Type: new Abstract: Continuous-time SLAM provides a principled framework for fusing heterogeneous sensors while estimating smooth trajectories, and is particularly well-sui

BRepCLIP: Contrastive Multimodal Pretraining on BRep Primitives for CAD Understanding

arXiv:2606.05515v1 Announce Type: new Abstract: Learning representations of CAD models is a largely open problem. While 3D representation learning has flourished around point clouds and meshes, the na

researcharxiv-cs-cv