Search: “evaluation”

Beyond 'To whom it may concern': Tailoring Machine Translation to Audience and Intent

arXiv:2606.03259v1 Announce Type: new Abstract: Translation quality depends on purpose: the same source text demands different translations depending on audience, tone, and communicative intent. Yet M

researcharxiv-cs-cl

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Building Better Activation Oracles

DGX agent

arXiv:2606.02609v1 Announce Type: cross Abstract: Activation Oracles (AOs) are promising methods for interpreting residual stream activations. However, current AOs face important issues, such as hallu

safetyarxiv-cs-ai

3 Jun 2026

Applications

Core-based Hierarchies for Efficient GraphRAG

arXiv:2603.05207v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models by incorporating external knowledge. However, existing vector-based method

applicationsarxiv-cs-cl

Cosmos 3: Omnimodal World Models for Physical AI

arXiv:2606.02800v1 Announce Type: cross Abstract: We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences

Coupled Local and Global World Models for Efficient First Order RL

arXiv:2602.06219v2 Announce Type: replace-cross Abstract: World models offer a promising avenue for more faithfully capturing complex dynamics, including contacts and non-rigidity, as well as complex

local-aiarxiv-cs-ai

CREward: A Type-Specific Creativity Reward Model

arXiv:2511.19995v2 Announce Type: replace Abstract: Creativity is a complex phenomenon. When it comes to representing and assessing creativity, treating it as a single undifferentiated quantity would

Cross-Lingual Token Arbitrage: Optimizing Code Agent Context Windows via Local LLM Preprocessing

arXiv:2606.03618v1 Announce Type: new Abstract: AI-assisted coding agents are bottlenecked by input-token cost. Two pathologies of raw human input drive much of this overhead: tokenization inefficienc

Tutorials

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures

arXiv:2606.02912v1 Announce Type: cross Abstract: Forecasting seismic waveforms beyond observed data remains challenging due to the nonlinear, dispersive, and multi-scale nature of seismic wave propag

tutorialsarxiv-cs-lg

DDOR: Delta Debugging for Explainable Overrefusal Testing and Repair

arXiv:2606.03601v1 Announce Type: cross Abstract: While safety alignment and guardrails help large language models (LLMs) avoid harmful outputs, they can also induce overrefusal, i.e., unwarranted rej

local-aiarxiv-cs-ai

DeskCraft: Benchmarking Desktop Agents on Professional Workflows and Human-in-the-Loop Collaboration

arXiv:2606.03103v1 Announce Type: new Abstract: Real-world professional desktop workflows in specialized creative and engineering software unfold over long horizons and often require human-in-the-loop

Diffusing in the Right Space: A Systematic Study of Latent Diffusability

arXiv:2606.03578v1 Announce Type: new Abstract: Latent diffusion models leverage visual tokenizers to compress images into latent spaces for efficient generative modeling. However, better reconstructi

researcharxiv-cs-cv

Disentangling Visual and Factual Correctness in LVLMs' Visualization Literacy

arXiv:2606.03142v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) show strong visualization interpretation, yet it is unclear whether their responses reflect genuine reasoning over

ERP-XTTN: Interpretable Prototype-Guided Cross-Attention for Cross-Subject ERP Classification

model-releasesarxiv-cs-lg

arXiv:2606.02939v1 Announce Type: new Abstract: Interpretable brain-computer interface classifiers that generalize across subjects without calibration remain an open challenge. We test whether prototy

EvoDrive: Pareto Evolution for Safety-Critical Autonomous Driving via Self-Improving LLM Agents

arXiv:2606.03678v1 Announce Type: new Abstract: Generating safety-critical scenarios is essential for validating and improving autonomous driving systems, yet it inherently requires maximizing adversa

Agents

EvoTrainer: Co-Evolving LLM Policies and Training Harnesses for Autonomous Agentic Reinforcement Learning

arXiv:2606.03108v1 Announce Type: new Abstract: Autonomous LLM training is often framed as recipe search, which leaves the training harness largely static. This limitation sharpens in agentic RL, wher

agentsarxiv-cs-ai

Finding Needles in the Haystack: Transductive Active Labeling in Ecology

arXiv:2606.03821v1 Announce Type: new Abstract: Active learning is now standard practice in labeling ecological data, enabling ecologists to quickly process large volumes of field data to understand a

researcharxiv-cs-lg

FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance

model-releasesarxiv-cs-lg

arXiv:2606.03184v1 Announce Type: cross Abstract: Financial forecasting is difficult due to low signal-to-noise ratios, latent factors, heavy tails, regime shifts, and jumps. Real-world benchmarks off

Follow-Your-Preference++: Rethinking Preference Alignment for Image Inpainting

arXiv:2606.03216v1 Announce Type: new Abstract: We study preference alignment for image inpainting. Rather than proposing yet another method, we revisit the problem from first principles and reassess

safetyarxiv-cs-cv

Forgetting is Not Erasure: Recovering Latent Knowledge via Transport Keys

arXiv:2606.02860v1 Announce Type: cross Abstract: Catastrophic forgetting is often framed as a representational problem: after sequential training, a model appears to lose the features that supported

safetyarxiv-cs-ai

Framing Migration News with LLMs: Structured CoT as a Support for Human Interpretation

arXiv:2606.03761v1 Announce Type: new Abstract: Frame analysis of migration news is a socially consequential task: media scholars and researchers who study how migration is narrated need tools that ar

local-aiarxiv-cs-cl

From Local Training to Large-Scale Mapping: A Comparative Assessment of Machine Learning and Deep Learning for Transferable Satellite-Derived Bathymetry

arXiv:2606.02764v1 Announce Type: new Abstract: Satellite-derived bathymetry (SDB) from multispectral imagery is cost-effective but scales poorly across regions, especially in optically complex coasta

Fully Automated Identification of Lexical Alignment and Preference-Stage Shifts in Large Language Models

arXiv:2606.03165v1 Announce Type: cross Abstract: The language used by digital chat assistants such as ChatGPT can diverge from human expectations (misalignment). Research, mostly on Scientific Englis

Greener Than Humans? Environmental Attitudes in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2606.02741v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in sustainability-related decision support, reporting, and public communication, yet little systemati

Hedge-Bench: Benchmarking Agents on Hard, Realistic Tasks Pertaining to Financial Reasoning

arXiv:2606.03918v1 Announce Type: new Abstract: AI agents can increasingly handle the mechanical tasks of financial analysis: retrieving documents, calculating formulas, updating spreadsheets. The har

High-Precision APT Malware Attribution with Out-of-Scope Resilience

arXiv:2606.03523v1 Announce Type: cross Abstract: Early attribution of Advanced Persistent Threat (APT) activity can help defenders prioritise investigation, select countermeasures, and reduce the imp

researcharxiv-cs-ai

Agents

Human-Like Goalkeeping in a Realistic Football Simulation: a Sample-Efficient Reinforcement Learning Approach

arXiv:2510.23216v4 Announce Type: replace Abstract: While several high profile video games have served as testbeds for Deep Reinforcement Learning (DRL), this technique has rarely been employed by the

agentsarxiv-cs-ai

InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain

arXiv:2606.03329v1 Announce Type: new Abstract: Long-context tasks require LLMs to identify and preserve answer-relevant information from large contexts. Chunk-wise memory agents address this issue by

local-aiarxiv-cs-ai

JAVEDIT: Joint Audio-Visual Instruction-Guided Video Editing with Agentic Data Curation

arXiv:2606.03168v1 Announce Type: new Abstract: While instruction-based video editing has seen significant progress, joint audio-visual editing remains constrained by the absence of dedicated datasets

KletterMix: Climbing Toward High-Quality German Pretraining Data

arXiv:2606.03773v1 Announce Type: new Abstract: High-quality pretraining data is a central ingredient in modern language models, but German-language resources remain far less developed than their Engl

researcharxiv-cs-cl

Learning Power Flow with Confidence: A Probabilistic Guarantee Framework for Voltage Risk

arXiv:2308.07867v4 Announce Type: replace-cross Abstract: The absence of formal performance guarantees in machine learning (ML) has limited its adoption for safety-critical power system applications,

safetyarxiv-cs-lg

Agents

MariData: One-Step Unpaired Image Translation for Maritime Environments

arXiv:2606.03246v1 Announce Type: new Abstract: The development on robust perception systems for Maritime Autonomous Surface Ships (MASS) is heavily constrained by the scarcity of diverse training dat

agentsarxiv-cs-cv

OVO-S-Bench: A Hierarchical Benchmark for Streaming Spatial Intelligence in Multimodal LLMs

arXiv:2606.03890v1 Announce Type: new Abstract: Multimodal agents in robotics, AR, and autonomous driving must reason about places and layouts from continuous egocentric streams, often using evidence

Plan, Verify and Fill: A Structured Parallel Decoding Approach for Diffusion Language Models

arXiv:2601.12247v3 Announce Type: replace-cross Abstract: Diffusion Language Models (DLMs) present a promising non-sequential paradigm for text generation, distinct from standard autoregressive (AR) a

Position: Adversarial ML for LLMs Is Not Making Any Progress

arXiv:2502.02260v2 Announce Type: replace Abstract: In the past decade, considerable research effort has been devoted to securing machine learning (ML) models that operate in adversarial settings. Yet

researcharxiv-cs-lg

RealClawBench: Live OpenClaw Benchmarks from Real Developer-Agent Sessions

model-releasesarxiv-cs-cl

arXiv:2606.03889v1 Announce Type: new Abstract: Agent benchmarks should reflect what users actually ask deployed agents to do, yet existing benchmarks often miss key realism properties of real develop

Reconstructing Objects along Hand Interaction Timelines in Egocentric Video

arXiv:2512.07394v2 Announce Type: replace Abstract: We introduce the task of Reconstructing Objects along Hand Interaction Timelines (ROHIT). We first define the Hand Interaction Timeline (HIT) from a

Reliability-Guided Depth Fusion for Glare-Resilient Navigation Costmaps

model-releasesarxiv-cs-ro

arXiv:2606.03421v1 Announce Type: new Abstract: Specular glare on reflective floors, glass boundaries, and glossy indoor surfaces frequently corrupts active-stereo RGB-D depth measurements, producing

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression

arXiv:2606.03465v1 Announce Type: cross Abstract: Post-training compression is essential for deploying large language models (LLMs) under tight resource constraints. Tensor decompositions have emerged

researcharxiv-cs-ai

Safety Measurements for Fine-tuned LLMs Should be Grounded in Capability

arXiv:2606.03648v1 Announce Type: cross Abstract: Adapting foundation large language models to a user's task or preferred style through fine-tuning can result in compromising the model's safety. Previ

Scalable On-Hardware Training of Quantum Neural Networks and Application to Clinical Data Imputation

arXiv:2606.03517v1 Announce Type: cross Abstract: Training quantum neural networks (QNNs) on quantum hardware is currently bottlenecked by the cost of gradient estimation: standard parameter-shift met

Hardware

Scaling Multi Agent Reinforcement Learning for Underwater Acoustic Tracking via Autonomous Vehicles

arXiv:2505.08222v3 Announce Type: replace-cross Abstract: Autonomous vehicles (AVs) offer a cost-effective solution for scientific missions such as underwater tracking. Reinforcement learning (RL) has

hardwarearxiv-cs-ai

Self-Refining Agentic Reinforcement Learning for Vision-Conditioned UAV Navigation

arXiv:2606.03963v1 Announce Type: cross Abstract: Deep reinforcement learning has shown strong potential for enabling autonomous robots to learn complex navigational tasks. However, its practical use

safetyarxiv-cs-ai

State-Coupled Volatility in Latent Dynamical Systems: Recovery Under Partial Observation

model-releasesarxiv-cs-lg

arXiv:2606.02664v1 Announce Type: cross Abstract: Latent state-space models are widely used to study partially observed dynamical systems, yet most formulations assume that process variability is inde

The Word and the Way: Strategies for Domain-Specific BERT Pre-Training in German Medical NLP

model-releasesarxiv-cs-cl

arXiv:2606.03250v1 Announce Type: new Abstract: Digital healthcare generates vast amounts of clinical text that can support AI-assisted applications, yet German biomedical language models remain limit

Tiny Collaborative Inference for Occlusion-Robust Object Detection

arXiv:2606.02894v1 Announce Type: new Abstract: Small edge devices such as IoT surveillance nodes and search-and-rescue (SAR) platforms are increasingly expected to run computer vision locally. On ult

local-aiarxiv-cs-cv

Translating Classical Poetry into Modern Prose

arXiv:2606.02806v1 Announce Type: new Abstract: We introduce Padyam2Gadyam, a dataset for the task of poem-to-prose translation from 13th-17th Century Telugu Classical Poetry to contemporary Telugu an

researcharxiv-cs-cl

TSQAgent: Rating Time Series Data Quality via Dedicated Agentic Reasoning

arXiv:2606.03629v1 Announce Type: new Abstract: Assessing the quality of time series (TS) data is fundamental yet inherently challenging due to the multifaceted nature of quality dimensions. Recently,

Typhoon: Towards an Effective Task-Specific Masking Strategy for Pre-trained Language Models

arXiv:2303.15619v2 Announce Type: replace-cross Abstract: The choice of which tokens to mask is a central, under-examined design decision in masked language modeling (MLM). Standard pretraining masks

researcharxiv-cs-ai