Search: “evaluation”

GLAN-QnA-KR: A Seedless Taxonomy-Driven Korean Instruction Corpus

model-releasesarxiv-cs-cl

arXiv:2607.20443v1 Announce Type: new Abstract: We release GLAN-QnA-KR, a 303,581-row openly redistributable Korean instruction-QA corpus produced via the seedless taxonomy-driven GLAN synthesis pipel

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Gradient Concentration, Not Weight Saliency, Explains Representation-Level Class Unlearning

DGX agent

arXiv:2607.21353v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of specific training data while preserving model utility. Many state-of-the-art approaches pursue this g

model-releasesarxiv-cs-lg

24 Jul 2026

GuardianAgentBench: Where Agents Fail and How to Guard Them

arXiv:2607.20982v1 Announce Type: new Abstract: As large language model agents increasingly operate autonomously with access to tools and external environments, ensuring their safe and reliable behavi

Agents

HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors

arXiv:2607.21281v1 Announce Type: new Abstract: Topological maps are key outputs of autonomous driving perception systems, delivering essential road information for path planning. They identify instan

agentsarxiv-cs-cv

HyperImageNet: A Large-Scale High-Spatial Resolution Hyperspectral Imagery Classification Benchmark

arXiv:2607.21050v1 Announce Type: new Abstract: We present HyperImageNet, a large-scale benchmark for fine-grained hyperspectral land-cover understanding. The dataset contains 26,084 airborne hyperspe

HyWorldVLA: A Vision-Language-Action Model with Hybrid World Modeling for Autonomous Driving

arXiv:2607.20988v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models augmented with world modeling represent a promising paradigm for end-to-end autonomous driving. While pixel-level

Agents

i2Nav-Robot: A Large-Scale Indoor-Outdoor Robot Dataset for Multi-Sensor Fusion Navigation

arXiv:2508.11485v3 Announce Type: replace Abstract: Accurate and reliable navigation is crucial for autonomous unmanned ground vehicles (UGVs). However, current UGV datasets fall short in meeting the

agentsarxiv-cs-ro

Applications

Improving Access to Essential Medicines via Decision-Aware Machine Learning

arXiv:2607.20542v1 Announce Type: cross Abstract: A critical challenge in healthcare systems in low- and middle-income countries (LMICs) is the efficient and equitable allocation of scarce resources,

applicationsarxiv-cs-ai

Is Deep Research Reliable? Misleading Knowledge Induces False Conclusions

arXiv:2607.20891v1 Announce Type: new Abstract: Deep Research agents extend LLM-based assistants into long-horizon workflows involving planning, retrieval, evidence synthesis, and report generation, y

Isolating LLM Alignment from Regex: Zero Coverage and Metric-Dependent Divergence Under Adversarial Mutation

arXiv:2607.20494v1 Announce Type: new Abstract: Production LLM applications commonly stack a regex filter in front of model-side alignment; prior work found no measurable coverage gain from adding a l

KeySI: An Interaction Framework for Tuning Text Embeddings Based on Human Feedback

arXiv:2607.20556v1 Announce Type: new Abstract: In large-scale text analysis tasks, pre-trained language models are often used to embed text corpora for downstream analysis. However, such models may s

Learning to Navigate Efficiently with Only 0.58M Trainable Parameters

arXiv:2607.11029v2 Announce Type: replace-cross Abstract: Recent progress in visual navigation has largely been driven by scale: end-to-end policies with hundreds of millions of parameters trained on

Loss Landscape Topology Reveals Why Simple Baselines are Competitive at 3D Point Cloud Segmentation Under Class Imbalance

arXiv:2607.21089v1 Announce Type: new Abstract: Semantic segmentation of 3D point clouds faces severe class imbalance, yet the effectiveness of specialized imbalance-aware methods from 2D computer vis

Tutorials

M^3-Gen: Interpretable Multimodal Generation of Gene Expression Profiles Using Clinical and Imaging Data

arXiv:2607.21343v1 Announce Type: cross Abstract: Integrating heterogeneous biomedical data, including clinical metadata, histopathology images, and molecular profiles, is crucial for comprehensive di

tutorialsarxiv-cs-ai

Local Ai

Machine Learning for Charge State Characterization of Isolated Double Quantum Dots

arXiv:2607.20871v1 Announce Type: cross Abstract: Scaling semiconductor quantum dot arrays toward fault-tolerant quantum computing requires efficient tuneup of spin qubits, a process that depends on t

local-aiarxiv-cs-lg

MAGE-Vein: Multi-Instance Age and Gender Estimation from Finger Vein Images

arXiv:2607.20897v1 Announce Type: new Abstract: Age estimation from finger vein images has been widely considered impractical due to severe demographic biases in public datasets and physiological conf

Tutorials

Making Open-Source Text LLM Watermarks Durable Against Merging

arXiv:2607.20435v1 Announce Type: cross Abstract: Open-source LLMs (OSMs)arereaching near state-of-the-art performance, prompting prior works to trace the text they generate by embedding text watermar

tutorialsarxiv-cs-ai

Mean-to-Score Discrete Diffusion: Posterior-Mean Denoisers for Score Entropy

arXiv:2607.21372v1 Announce Type: cross Abstract: Score Entropy Discrete Diffusion (SEDD) parameterizes discrete reverse processes with unconstrained positive score ratios. While positivity guarantees

MedGame: Storytelling Gamification Empowered by Large Language Models for Medical Education

model-releasesarxiv-cs-cl

arXiv:2607.21570v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise for medical education, but most existing systems focus on localized interactions such as question answering or

MO-GRPO: Mitigating Reward Hacking of Group Relative Policy Optimization on Multi-Objective Problems

model-releasesarxiv-cs-lg

arXiv:2509.22047v3 Announce Type: replace Abstract: Group Relative Policy Optimization (GRPO) has been shown to be an effective algorithm when an accurate reward model is available. However, such a hi

Local Ai

MSBraM: A Multi-scale Self-supervised Brain Foundation Model for Hierarchical EEG Dynamics Learning

arXiv:2607.21402v1 Announce Type: new Abstract: Self-supervised foundation models have recently shown strong potential for electroencephalogram (EEG)-based analysis. However, existing approaches strug

local-aiarxiv-cs-ai

Multi-Task Learning for Heterogeneous Prediction from Video Game State with Transfer Learning

arXiv:2607.21290v1 Announce Type: cross Abstract: Multi-task learning (MTL) is a promising approach for prediction tasks derived from video game state data, as modern game telemetry provides multiple

researcharxiv-cs-ai

Multi-turn RL with Structural and Performance Aware Rewards for CUDA Kernel Generation

arXiv:2607.20908v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a powerful technique to enhance the reasoning capacity of LLMs for optimized code

Multilevel Graph Wavelet Compressed Sensing with Scale-Aware Neural Recovery

arXiv:2607.20857v1 Announce Type: cross Abstract: Scientific machine learning methods such as neural operators and physics-informed neural networks have advanced engineering applications and inverse p

researcharxiv-cs-ai

Multimodal CoLRAG-TF: Triple-Filtered Retrieval for Complex PDFs

model-releasesarxiv-cs-lg

arXiv:2607.20517v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) over heterogeneous PDF collections remains challenging due to multimodal content, domain-specific terminology, and

news-crawler-LM: A Small Long-Context Model For High-Quality News Crawling

arXiv:2607.21284v1 Announce Type: new Abstract: Extracting structured content from news pages remains challenging due to heterogeneous HTML layouts, inconsistent markup, and substantial boilerplate su

researcharxiv-cs-cl

ODeform: Learning Continuous 4D Motion for Shape Deformation with Neural ODEs

arXiv:2607.20670v1 Announce Type: new Abstract: Modeling continuous object deformation is important for many computer vision and robotics tasks, such as manipulation and simulation. Existing approache

One More Turn, Less Regret: A Regret-Based Multi-Turn Benchmark for LLMs' Clarification Policies

arXiv:2607.21143v1 Announce Type: cross Abstract: Ambiguous user requests make clarification a sequential decision problem for conversational LLM assistants: they must decide whether to ask, what to a

Operational Identity: A Finite Audit of Declared and Implemented Rules of Sameness

arXiv:2607.20729v1 Announce Type: cross Abstract: A record system declares when two records refer to the same entity, occurrence, scope, or rule. Its disclosed implementation mechanisms induce a corre

OPOD: On-Policy Omni Distillation

arXiv:2607.20918v1 Announce Type: new Abstract: Omni-modal models can handle text, images, and audio in one system, but improving all of these abilities together remains difficult. Training a single m

Opus 5 is a great model for coding, data analysis, design, biology, knowledge work. More than any of these eval scores, what is most excitin…

model-releasesboris-cherny--x

Opus 5 is a great model for coding, data analysis, design, biology, knowledge work. More than any of these eval scores, what is most exciting to me is something else: Opus 5 is our least prompt inject

PATS: Policy-Aware Training Scaffolding for Agentic Reinforcement Learning

arXiv:2607.21419v1 Announce Type: new Abstract: In long-horizon LLM agent reinforcement learning, weak policies often repeat similar failures, producing uninformative rollout trajectories and limiting

PersonaGesture: Single-Reference Co-Speech Gesture Personalization for Unseen Speakers

arXiv:2605.06064v2 Announce Type: replace Abstract: We propose PersonaGesture, a diffusion-based pipeline for single-reference co-speech gesture personalization of unseen speakers. Given target speech

PersonaTrail: Benchmarking Personalized Web Agents through Browsing Trails

arXiv:2607.20482v1 Announce Type: new Abstract: Recent advances in large language models have enabled web agents to autonomously execute complex tasks. In practice, users frequently provide underspeci

Physics-Informed Deep Learning Model for Cross-Modality Super-Resolution in Fluorescence Microscopy

arXiv:2607.21190v1 Announce Type: new Abstract: Cross-modality image translation offers a route to super-resolution fluorescence microscopy from low-resolution images while reducing phototoxicity and

ProCap: Prominence-guided Object Rectification for Faithful and Comprehensive Video Captioning

arXiv:2607.21022v1 Announce Type: new Abstract: Improving video captioning quality typically demands retraining large vision-language models, an expensive and often impractical requirement. Existing t

Profiling Lightweight Large Language Models

arXiv:2607.20806v1 Announce Type: new Abstract: Lightweight large language models (LLMs) are increasingly being deployed locally on personal computers and are expected to play a growing role in resour

Progressive Cramming: Reliable Token Compression and What It Reveals

arXiv:2607.21231v1 Announce Type: new Abstract: Token cramming compresses sequences into learned embeddings with near-perfect reconstruction, but fixed token budgets and 99% accuracy thresholds leave

researcharxiv-cs-cl

PromptPack: Scaling LLM Annotation Agents for Online Recommendation

arXiv:2607.20528v1 Announce Type: new Abstract: Online recommendation platforms increasingly use Large Language Models (LLMs) to extract structured features from ad creatives. While deploying a single

Tutorials

Quality-Aware Multimodal Fusion Reveals Implicit Identity in Valence-Arousal Features

arXiv:2607.21347v1 Announce Type: new Abstract: Conventional face recognition relies on static appearance cues and degrades in unconstrained settings with expression variation, occlusion, and poor lig

tutorialsarxiv-cs-cv

RE-AD: Real-Time Requirement Adherence for Data Labeling

arXiv:2607.20455v1 Announce Type: cross Abstract: Human-annotated data remains fundamental to training frontier Large Language Models (LLMs). However, crowd-sourced annotations often suffer from quali

Recurrent Sinusoidal INRs for Efficient High-Fidelity Representation

arXiv:2607.21485v1 Announce Type: new Abstract: We study sinusoidal recurrence as an iterative mechanism for harmonic spectral enrichment in implicit neural representations (INRs). Our analysis reveal

Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers

arXiv:2607.21010v1 Announce Type: new Abstract: Zero-shot summarization using Large Language Models (LLMs) has significantly advanced the abstractive summarization task by producing coherent and fluen

Applications

ReliableTableQA:How Much Supervision Does Reliability Annotation Need?

arXiv:2607.20537v1 Announce Type: cross Abstract: We introduce ReliableTableQA, a framework for training an LLM to annotate the statistical reliability of tabular QA results, not whether the query is

applicationsarxiv-cs-ai

Robust Critics: Defending LLMs Against Multi-Turn Attacks

arXiv:2607.20472v1 Announce Type: new Abstract: When a user asks a language model something harmful, is it a genuine attack or a misunderstood but well-meaning question? This ambiguity is one of the c

RUMBA: Russian User Memory Benchmark

arXiv:2607.21447v1 Announce Type: cross Abstract: The ability to handle long-term memory in LLMs is becoming increasingly critical, yet existing benchmarks remain English-centric and rely on aggregate

Safe and Scalable Multi-Drone Payload Transport via CBF-based Reinforcement Learning with Zero-Shot Sim-to-Real Transfer

arXiv:2607.20665v1 Announce Type: new Abstract: Multi-drone payload transportation has emerged as a promising research paradigm with potential applications in construction, logistics, and disaster res

safetyarxiv-cs-ro

Applications

Safeguards for Speech2Speech LLM-Assistants: A Case Study in Automotive Applications

arXiv:2607.21180v1 Announce Type: new Abstract: Recent advances have introduced speech-to-speech (S2S) conversational assistants capable of producing natural-sounding interactions, including non-verba

applicationsarxiv-cs-ai