Search: “evaluation”

Interpreting Style Representations via Style-Eliciting Prompts

arXiv:2606.05716v1 Announce Type: new Abstract: Style representation learning is a powerful tool for authorship analysis and modeling writing style, yet the latent nature of learned representations ma

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Inverse Manipulation through Symbolic Planning and Residual Operator Learning

DGX agent

arXiv:2606.05248v1 Announce Type: new Abstract: Inverting a robotic task requires more than reversing symbolic state transitions or rewinding motor trajectories. In robot manipulation tasks, symbolic

safetyarxiv-cs-ro

5 Jun 2026

IR3DE: A Linear Router for Large Language Models

arXiv:2606.06098v1 Announce Type: new Abstract: Foundational Large Language Models (LLMs) demonstrate proficiency on a wide range of general tasks, and achieve remarkable results on various specialize

L-SDPPO: Policy Optimization of Spiking Diffusion Policy for Intra-vehicular Robotic Manipulation

arXiv:2606.06049v1 Announce Type: new Abstract: Intra-vehicular robots in spacecraft help reduce astronaut workload and improve mission efficiency. Recent research focuses on using deep learning metho

safetyarxiv-cs-ro

Applications

LANTERN: Layered Archival and Temporal Episodic Retrieval Network for Long-Context LLM Conversations

arXiv:2606.05182v1 Announce Type: new Abstract: Large language models discard critical details when conversation history is compacted to fit within finite context windows. We present LANTERN (Layered

applicationsarxiv-cs-cl

Local Ai

LeanMarathon: Toward Reliable AI Co-Mathematicians through Long-Horizon Lean Autoformalization

arXiv:2606.05400v1 Announce Type: cross Abstract: Long-horizon autoformalization of research mathematics fails not only at hard lemmas, but at scale: statements drift, dependencies tangle, context dec

local-aiarxiv-cs-cl

Applications

Learning Predictive Visuomotor Coordination

arXiv:2503.23300v2 Announce Type: replace Abstract: Understanding and predicting human visuomotor coordination is crucial for applications in robotics, human-computer interaction, and assistive techno

applicationsarxiv-cs-cv

Less is MoE: Trimming Experts in Domain-Specialist Language Models

arXiv:2606.05538v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models achieve strong performance through conditional computation, but their large parameter footprint poses deployment chall

Let It Be Simple: One-Step Action Generation for Vision-Language-Action Models

arXiv:2606.05737v1 Announce Type: new Abstract: Diffusion-based vision-language-action (VLA) models often inherit the image-generation view: actions are generated by iterative denoising. We argue that

Leveraging Large Language Models for Generating Research Topic Ontologies: A Multi-Disciplinary Study

arXiv:2508.20693v2 Announce Type: replace-cross Abstract: Ontologies and taxonomies of research fields are critical for managing and organising scientific knowledge, as they facilitate efficient class

LiAuto-GeoX: Efficient Grounded Driving Transformer

arXiv:2606.05774v1 Announce Type: new Abstract: Dense 3D reconstruction has demonstrated immense potential for spatial understanding, yet its viability as a real-time, onboard representation for auton

LightVesselNet: An Ultra-Lightweight Sub-100K Parameter Network for Retinal Blood Vessel Segmentation

arXiv:2606.05354v1 Announce Type: new Abstract: Retinal blood vessel segmentation plays a vital role in the early detection of diabetic retinopathy and glaucoma. While recent deep learning models have

Localizing Prompt Ambiguity in Large Language Models with Probe-Targeted Attribution

arXiv:2606.05486v1 Announce Type: new Abstract: Prompt ambiguity is a common source of failure in large language models, but is difficult to localize because it is a latent property of the prompt, whi

LongSpace: Exploring Long-Horizon Spatial Memory from Perception to Recall in Video

arXiv:2606.05677v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have advanced image and video understanding and can increasingly handle longer visual inputs. Long-horizon ta

LoRi: Low-Rank Distillation for Implicit Reasoning

arXiv:2606.05315v1 Announce Type: new Abstract: Implicit chain-of-thought (iCoT) methods aim to internalize reasoning in large language models, but often underperform explicit CoT prompting. We empiri

MAviS: A Multimodal Conversational Assistant For Avian Species

arXiv:2603.07294v2 Announce Type: replace Abstract: Fine-grained understanding and species-specific multimodal question answering are vital for advancing biodiversity conservation and ecological monit

MCBench: A Multicontext Safety Assessment Benchmark for Omni Large Language Models

arXiv:2606.05177v1 Announce Type: new Abstract: Existing multimodal safety benchmarks focus solely on visual inputs and cannot assess Omni Large Language Models (LLMs) that process vision, audio, and

MDP-GRPO: Stabilized Group Relative Policy Optimization for Multi-Constraint Instruction Following

arXiv:2606.06058v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards is ideal for multi-constraint instruction following, yet standard group-relative policy optimization (G

MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery

arXiv:2606.06473v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery and machine learning engineering (MLE),

agentsarxiv-cs-cl

MPCoT: Reward-Guided Multi-Path Latent Reasoning for Test-Time Scalable Vision-Language-Action

arXiv:2606.06245v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies remain brittle in long-horizon and high-uncertainty control, where one-pass action decoding provides limited infer

researcharxiv-cs-ro

Multi-Resolution Tactile Imitation Learning for Contact-Rich Robotic Manipulation

arXiv:2606.06281v1 Announce Type: new Abstract: Touch sensing is beneficial for solving a wide variety of manipulation tasks. While there exists a wide range of tactile sensors with different properti

safetyarxiv-cs-ro

Next-Generation Parallel Decoder for LPDR: Architectural Optimization and Class-Balanced GAN-Augmentation

arXiv:2606.05785v1 Announce Type: new Abstract: Real-Time License Plate Detection and Recognition (LPDR) forms the backbone of modern smart cities. Although the YOLOV5-PDLPR model substantially improv

researcharxiv-cs-cv

Tools

OpenAI Help: Lockdown Mode

OpenAI Help: Lockdown Mode OpenAI first teased this in February, but now it's live and 'rolling out to eligible personal accounts, including Free, Go, Plus, and Pro, and self-serve ChatGPT Business ac

toolssimon-willison

Operation-Guided Progressive Human-to-AI Text Transformation Benchmark for Multi-Granularity AI-Text Detection

arXiv:2606.06481v1 Announce Type: new Abstract: As AI writing assistants become increasingly integrated into real-world drafting and revision workflows, many documents are no longer purely human-writt

OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation

arXiv:2606.06096v1 Announce Type: cross Abstract: Policy-gradient methods usually optimize expected return, but many real world applications care about distributional properties of returns: tail risk,

safetyarxiv-cs-cl

PAR3D: A Unified 3D-MLLM with Part-Aware Representation for Scene Understanding

arXiv:2606.06485v1 Announce Type: new Abstract: Recent advances in 3D multimodal large language models (3D-MLLMs) have enabled unified solutions for 3D scene understanding tasks, including visual ques

researcharxiv-cs-cv

Physics-Guided Deep Unfolding for Blind Cross-Sensor Spectral Super-Resolution via Learning the Spectral Transformation Function

arXiv:2606.05759v1 Announce Type: new Abstract: Hyperspectral imaging provides rich spectral information for quantitative remote sensing, yet hyperspectral sensors remain costly and thus unavailable i

Political appointees vetting science funding? Trump is doing to science what the Right accused previous administrations of doing. But in pre…

Political appointees vetting science funding? Trump is doing to science what the Right accused previous administrations of doing. But in previous administrations, there was no political control of res

safetyyann-lecun--x

Predictable Scaling Laws of Optimal Hyperparameters for LLM Continued Pre-training

arXiv:2606.05610v1 Announce Type: new Abstract: The efficacy of continued pre-training for Large Language Models (LLMs) hinges upon hyperparameter configurations, such as learning rate and batch size.

Local Ai

ProSarc: Prosody-Aware Sarcasm Recognition Framework via Temporal Prosodic Incongruity

arXiv:2606.06168v1 Announce Type: cross Abstract: We present ProSarc, an audio-only framework that detects sarcasm by modelling temporal prosodic incongruity, that is, the mismatch between local proso

local-aiarxiv-cs-cl

QueryAgent-R1: Bridging Query Generation and Product Retrieval for E-Commerce Query Recommendation

arXiv:2606.05671v1 Announce Type: new Abstract: Query recommendation in e-commerce search aims to proactively suggest queries that match users' potential interests. However, existing methods mainly op

safetyarxiv-cs-cl

Real-Time Threat Detection from Surveillance Cameras using Machine Learning

arXiv:2606.05708v1 Announce Type: new Abstract: Ensuring public safety in densely populated urban environments remains a critical challenge, necessitating the deployment of intelligent and automated v

ReasoningFlow: Discourse Structures for Understanding LLM Reasoning Traces

arXiv:2606.05402v1 Announce Type: new Abstract: Large reasoning models (LRMs) produce reasoning traces with non-linear structures, such as backtracking and self-correction, that complicate the evaluat

ReSAGE-PAR: Representational Similarity Assessment for Generative Expansion in Pedestrian Attribute Recognition

arXiv:2606.06020v1 Announce Type: new Abstract: To address the limited diversity and data scarcity in Pedestrian Attribute Recognition (PAR), we explore image synthesis using diffusion models guided b

Resonant Minds: Closed-Loop Social Avatars with Theory of Mind

arXiv:2606.05896v1 Announce Type: new Abstract: Creating lifelike digital humans with genuine social intelligence requires unifying cognitive reasoning and multimodal generation within a coherent fram

agentsarxiv-cs-cv

Retrospective Harness Optimization: Improving LLM Agents via Self-Preference over Trajectory Rollouts

arXiv:2606.05922v1 Announce Type: cross Abstract: AI agents rely on a harness of skills, tools, and workflows to solve complex problems. Continually improving this harness is essential for adapting to

agentsarxiv-cs-cl

RoCA: Robust Cross-Domain End-to-End Autonomous Driving

arXiv:2506.10145v3 Announce Type: replace Abstract: End-to-end (E2E) autonomous driving has recently emerged as a new paradigm, offering significant potential. However, few studies have looked into th

agentsarxiv-cs-cv

Scaffold, Not Vocabulary? A Controlled, Two-Tier, Pre-Registered Study of a Popperian Code-Generation Skill

arXiv:2606.06454v1 Announce Type: cross Abstract: Large language models increasingly write, review, and judge code, and a fast-growing practice equips them with prompt 'skills' that ask the model to r

Self-supervised User Profile Generation for Personalization

arXiv:2606.05336v1 Announce Type: new Abstract: Personalizing large language models (LLMs) has become a central challenge as LLMs are deployed across recommendation, search, dialogue, and content gene

Local Ai

Statistical Priors for Implicit Preferences: Decoupling Skill Selection as a Local Harness in Personal Agents

arXiv:2606.05828v1 Announce Type: cross Abstract: As Large Language Model (LLM) capabilities advance, locally deployed personal agents relying on API-based remote models and external skills have emerg

local-aiarxiv-cs-cl

StoryVideoQA: Scaling Deep Video Understanding with a Large-Scale, Multi-Genre and Auto-Generated Dataset

arXiv:2606.06338v1 Announce Type: new Abstract: Video question answering (VideoQA) aims to answer questions about given videos. While existing approaches excel on factoid VideoQA, they struggle with d

Symb-xMIL: Symbolic Explanations for Multiple Instance Learning in Digital Pathology

arXiv:2606.06224v1 Announce Type: new Abstract: Explanations of multiple instance learning (MIL) models are widely used for validation and discovery in digital histopathology. Existing methods primari

TAM: Torque Adaptation Module for Robust Motion Transfer in Manipulation

arXiv:2606.06218v1 Announce Type: new Abstract: A policy tuned for one robot often behaves differently on another, whether due to the sim-to-real gap, unknown payloads, or the differing dynamics of tw

safetyarxiv-cs-ro

The Granularity Gap: A Multi-Dimensional Longitudinal Audit of Sycophancy in Gemini Models

arXiv:2606.05183v1 Announce Type: new Abstract: Large language models are increasingly deployed as high-stakes advisors, yet standard alignment benchmarks treat sycophancy as a binary failure mode. We

// The Meta-Agent Challenge // How good are current agents at self-improving? This is a great paper covering some of the challenges. They pr…

// The Meta-Agent Challenge // How good are current agents at self-improving? This is a great paper covering some of the challenges. They propose the Meta-Agent Challenge (MAC), where they give a codi

agentsdair-ai--x

The Mirage of Performance Gains: Why Contrastive Decoding Fails to Mitigate Object Hallucinations in MLLMs?

arXiv:2504.10020v4 Announce Type: replace Abstract: Contrastive decoding strategies are widely used to reduce object hallucinations in multimodal large language models (MLLMs). These methods work by c

Three-Dimensional Retinal Microvasculature Restoration in OCT Angiography

arXiv:2606.05375v1 Announce Type: new Abstract: Optical coherence tomographic angiography (OCTA) is a powerful technique for imaging retinal microvasculature. However, acquiring reliable quantificatio

researcharxiv-cs-cv

Applications

Towards Label-Noise Resistant Learning via Optimal Brain Damage Masking

arXiv:2508.09697v3 Announce Type: replace-cross Abstract: Noisy labels are inevitable in real-world scenarios. Due to the strong capacity of deep neural networks to memorize corrupted labels, these no

applicationsarxiv-cs-cv