Search: “evaluation”

PhoneBuddy: Training Open Models for Agentic Phone Use

arXiv:2606.23049v2 Announce Type: replace Abstract: Phones are becoming an important execution surface for general-purpose agents, but training open models for reliable phone use remains difficult bec

agentsarxiv-cs-cl

Privacy-Aware Visual Language Models

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arXiv:2405.17423v4 Announce Type: replace-cross Abstract: As Visual Language Models (VLMs) become increasingly embedded in everyday applications, ensuring they can recognise and appropriately handle p

model-releasesarxiv-cs-cl

25 Jun 2026

Re-mixing Embeddings for Patient Augmentation in Data Scarce Multiple Instance Learning

arXiv:2606.25770v1 Announce Type: cross Abstract: Data scarcity is a major bottleneck in medical Multiple Instance Learning (MIL), especially for rare diseases or expensive modalities. We introduce a

researcharxiv-cs-cv

Reasonable Motion: A General ASP Foundation for Environment Constrained Movement Trajectory Computation

model-releasesarxiv-cs-ro

arXiv:2606.25626v1 Announce Type: cross Abstract: We present a general answer set programming based hybrid quantitative-qualitative method for computing constrained branching trajectory modes for movi

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection

arXiv:2606.24985v1 Announce Type: new Abstract: Personalization in wearable-based stress detection remains challenging due to substantial inter-individual variability in physiological and behavioral r

researcharxiv-cs-lg

RevengeBench: Reverse Engineering Code-Space Policies from Behavioral Experiments

model-releasesarxiv-cs-lg

arXiv:2606.26094v1 Announce Type: new Abstract: For most of scientific history, researchers studying behavior could only infer hidden mechanisms from outward actions: an inverse problem that becomes m

Riazi-8B: An Urdu Large Language Model for Mathematical Reasoning

arXiv:2606.25568v1 Announce Type: new Abstract: Recent LLMs demonstrate strong mathematical reasoning capabilities, but existing gains rely heavily on English-centric training resources and benchmarks

researcharxiv-cs-cl

RoboAtlas: Contextual Active SLAM

arXiv:2606.26046v1 Announce Type: cross Abstract: We present RoboAtlas, a contextual Active SLAM framework that adaptively balances geometric exploration and semantic reasoning using a scalable 3D sem

S^{2}-FracMix: Label-Preserving Self-Saliency Mixup Augmentation

arXiv:2606.25784v1 Announce Type: new Abstract: Data augmentation is known to improve generalization of deep visual models. Recent methods favor mixup strategies that generate interpolated samples to

researcharxiv-cs-cv

SAC^2-Net: Semantic Anchoring and Complementary-Consensus Fusion for Multimodal Micro-Expression Recognition

arXiv:2606.25542v1 Announce Type: new Abstract: Micro-expression recognition (MER) is challenging due to subtle facial movements, limited data, and the ambiguous relationship between Action Units (AUs

safetyarxiv-cs-cv

SAGE-Nav: Leveraging LLM Planning and Alignment Fusion for Hierarchical Scene Graph-Guided Navigation

arXiv:2606.25497v1 Announce Type: new Abstract: Object-Goal Navigation (ObjNav) requires embodied agents to autonomously locate specified targets using only egocentric visual observations. Existing mo

safetyarxiv-cs-ro

Same Evidence, Different Answer: Auditing Order Sensitivity in Multimodal Large Language Models

arXiv:2606.26079v1 Announce Type: new Abstract: Standard benchmarks for multimodal large language models (MLLMs) score each item on one canonical ordering and miss whether order-irrelevant shuffling c

Scale or Reason? A Compute-Equivalent Analysis of Reasoning Distillation

arXiv:2509.22193v2 Announce Type: replace Abstract: Distilling reasoning traces from strong teacher models has become the standard recipe for building capable small language models. Yet reasoning trac

researcharxiv-cs-cl

SE-AGCNet: An End-to-End Framework for Joint Speech Enhancement and Loudness Control in Meeting Scenarios

arXiv:2606.25959v1 Announce Type: cross Abstract: Conventional audio pipelines typically treat speech enhancement (SE) and automatic gain control (AGC) as discrete modules, which often limits overall

researcharxiv-cs-ai

Self Capacitive Tactile Sensor System designed for Companion Robots

arXiv:2606.25348v1 Announce Type: new Abstract: Tactile sensing is essential for humanoid robots to achieve safe physical interaction, dexterous manipulation, and truly human-like responsiveness. Howe

researcharxiv-cs-ro

SFL-MTSC: Leveraging Semantic Frame-Level Multi-Task Self-Consistency for Robust Multi-Intent Spoken Language Understanding

arXiv:2606.25552v1 Announce Type: new Abstract: Prompt-based spoken language understanding (SLU) with large language models (LLMs) often suffers from inconsistent intent--slot structures due to decodi

SoK: AI Secure Code Generation: Progress, Pitfalls, and Paths Forward

arXiv:2606.25195v1 Announce Type: cross Abstract: The increasing use of AI systems for code generation raises a central security question: what can today's models and coding agents actually do to prod

agentsarxiv-cs-ai

SparseGS: Sparse View Synthesis using 3D Gaussian Splatting

arXiv:2312.00206v4 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has recently enabled real-time rendering of unbounded 3D scenes for novel view synthesis. However, this technique requi

researcharxiv-cs-cv

Spatio-Temporal Mixture-of-Modality-Experts Diffusion for Quantitative DCE-MRI Synthesis from Incomplete MR Sequences

arXiv:2606.25535v1 Announce Type: new Abstract: Quantitative maps from dynamic contrast-enhanced MRI (DCE-MRI) are essential for tumor assessment but are often unavailable due to contrast-agent risks

Specifying AI-SDLC Processes: A Protocol Language for Human-Agent Boundaries

arXiv:2606.20615v2 Announce Type: replace Abstract: AI agents now participate as first-class team members across the software development lifecycle, yet no specification language exists for expressing

safetyarxiv-cs-ai

Speech Codec Probing from Semantic and Phonetic Perspectives

arXiv:2603.10371v2 Announce Type: replace-cross Abstract: Speech tokenizers are essential for connecting speech to large language models (LLMs) in multimodal systems. Speech tokenizers are expected to

Spotlighting Task-Relevant Features: Object-Centric Representations for Better Generalization in Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2601.21416v2 Announce Type: replace Abstract: The generalization capabilities of robotic manipulation policies are heavily influenced by the choice of visual representations. Existing approaches

Stage-Aware and Roughness-Constrained Diffusion Policy for Multi-Stage Robotic Polishing

model-releasesarxiv-cs-ro

arXiv:2606.25754v1 Announce Type: new Abstract: Polishing is a critical finishing process in high-end manufacturing fields such as aerospace, where surface quality directly affects the service perform

Staying In Character: Perspective-Bounded Memory For Book-Based Role-Playing Agents

arXiv:2606.25632v1 Announce Type: new Abstract: Recent LLM role-playing systems build character agents from novels by extracting characters, scenes, and relations. Yet long-narrative role-playing suff

SurveilNav: Collaborative Object Goal Navigation with Robot and Surveillance System

arXiv:2606.25119v1 Announce Type: new Abstract: With the growing deployment of surveillance systems in factories, offices, and homes, integrating them with robots offers a promising direction for coll

agentsarxiv-cs-ro

Taxonomy-aware deep learning for hierarchical marine species classification in underwater imagery

arXiv:2606.25989v1 Announce Type: new Abstract: Automated classification of marine species from underwater imagery is essential for scalable ocean biodiversity monitoring and conservation policy. Exis

safetyarxiv-cs-cv

Tensorion: A Tensor-Aware Generalization of the Muon Optimizer

arXiv:2606.25975v1 Announce Type: cross Abstract: Common first-order optimizers, such as Adam, implicitly treat each parameter block as an unstructured vector, which disregards the multilinear weight

The Hitchhiker's Guide to Agentic AI: From Foundations to Systems

arXiv:2606.24937v1 Announce Type: cross Abstract: The Hitchhiker's Guide to Agentic AI is a comprehensive practitioner's reference for building autonomous AI systems. The book covers the full stack fr

safetyarxiv-cs-cl

The Interplay of Harness Design and Post-Training in LLM Agents

arXiv:2606.25447v1 Announce Type: cross Abstract: Tool-integrated LLM agents are often wrapped within a harness: the scaffolding that determines which tools are exposed, how they are described, and wh

researcharxiv-cs-cl

The Tatoxa System for Text Detoxification in Low-Resource Languages: The Case of Tatar

arXiv:2606.26015v1 Announce Type: new Abstract: Text detoxification, the automated detection and mitigation of abusive and harmful content, is essential for ensuring the safety of online communities a

safetyarxiv-cs-cl

The Unfireable Safety Kernel: Execution-Time AI Alignment for AI Agents and Other Escapable AI Systems

arXiv:2606.26057v1 Announce Type: cross Abstract: AI agents are granted access to tools, APIs, and other infrastructure, making them active principals in those systems. The dominant approach places co

Toten: A Knowledge-Based System For Structure-Preserving Representation Of Physical Quantities And Technical Notation In Brazilian Portuguese

arXiv:2606.19626v2 Announce Type: replace-cross Abstract: AI pipelines that reason quantitatively over technical text depend on input where physical quantities, numbers, units, and symbolic expression

Applications

Towards Continuous Power Forecasting: Practical Continual Learning for Real-World Energy Systems in Nonstationary Time Series

arXiv:2606.24955v1 Announce Type: new Abstract: Power forecasting models deployed in real-world energy markets must operate under nonstationary conditions, where data distributions continually evolve

applicationsarxiv-cs-lg

Towards Scalable Multi-Task Reinforcement Learning with Large Decision Models

arXiv:2606.24962v1 Announce Type: new Abstract: Recent progress in large-scale sequence modeling has shown that a single model can learn useful representations across highly diverse data distributions

Training for the Model You Return: Improving Optimization for Iterate-Averaged Language Models

model-releasesarxiv-cs-lg

arXiv:2606.25086v1 Announce Type: new Abstract: Many modern Language Model (LM) pipelines return an averaged model, such as an exponential moving average of the training iterates, rather than the fina

TriViewBench: Controlled Complexity Scaling for Multi-View Structural Reasoning in MLLMs

arXiv:2606.26029v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) demonstrate strong performance on standard visual question answering benchmarks, yet their scalability under co

TRUSTMEM: Learning Trustworthy Memory Consolidation for LLM Agents with Long-Term Memory

arXiv:2606.25161v1 Announce Type: new Abstract: Large language model (LLM) agents rely on long-term memory to support extended interactions and personalized assistance beyond finite context windows. E

researcharxiv-cs-ai

Uncertainty-aware reinforcement learning for chemical language models

arXiv:2606.24990v1 Announce Type: new Abstract: Reinforcement Learning (RL) has become a powerful paradigm for de novo molecular design, enabling Chemical Language Models (CLMs) to navigate and explor

Uncertainty Quantification for Computer-Use Agents: A Benchmark across Vision-Language Models and GUI Grounding Datasets

arXiv:2606.25760v1 Announce Type: cross Abstract: Computer-use agents turn vision-language model (VLM) predictions into executable GUI clicks, so reliable uncertainty estimates are essential for rejec

V-Zero: Answer-Label-Free On-Policy Distillation with Contrastive Evidence Gating for Fine-Grained Visual Reasoning

arXiv:2606.25319v1 Announce Type: new Abstract: Fine-grained visual reasoning requires multimodal large language models (MLLMs) to identify task-relevant visual evidence and ground their reasoning in

VADAOrchestra: Neurosymbolic Orchestration of Adaptive Reasoning Workflows

arXiv:2606.22485v2 Announce Type: replace-cross Abstract: Decision-making in real-world settings rarely follows a fixed script. Instead, it unfolds as a dynamic reasoning process in which the appropri

agentsarxiv-cs-cl

Variational Inference via Entropic Transport Descent

arXiv:2606.25265v1 Announce Type: new Abstract: Particle-based variational inference (ParVI) methods approximate an intractable target distribution by evolving an ensemble of interacting samples. Exis

researcharxiv-cs-lg

Velocity Prediction in Automatic Guitar Transcription

arXiv:2606.24912v1 Announce Type: cross Abstract: Automatic Music Transcription (AMT) models have achieved a high level of success in polyphonic transcription of various instruments. Velocity, typical

researcharxiv-cs-ai

Verifiable Manifest Signing and Transparency Enforcement for Secure MCP-Based LLM Pipelines

model-releasesarxiv-cs-ai

arXiv:2601.23132v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in tool-driven environments such as healthcare analytics, financial systems, retrieval-

VPA-Guard: Defending and Benchmarking Image-to-Video Generation Against Visual Prompt Attacks

arXiv:2606.25592v1 Announce Type: new Abstract: Recent advancements in Image-to-Video (I2V) generation have transformed input images from simple appearance references into interactive control interfac

What Does the Brain See? Multiview Neural Representations to Demystify the Brain-Visual Alignment

arXiv:2606.25718v1 Announce Type: new Abstract: Zero-shot visual decoding from electroencephalography (EEG) aims to infer visual semantics from non-invasive neural recordings, but remains challenging

Industry

What To Look For in a Serverless Database for AI Applications

A serverless database for AI applications should prioritize scalability, low latency, and seamless integration with machine learning workflows, eliminating the need for infrastructure management. Key

industrydatabricks

When Do Conservation Laws Survive Learned Representations? Certified Horizons for Latent World Models

arXiv:2606.24945v1 Announce Type: new Abstract: We ask a representation-learning question about physical world models: when does a conservation law remain certifiable after a model learns a latent rep