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arXiv:2509.00789v2 Announce Type: replace Abstract: The pursuit of autonomous agents capable of temporally coherent planning is hindered by a fundamental flaw in current vision-language models (VLMs):

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Research

Countdown-Code: A Testbed for Studying The Emergence and Generalization of Reward Hacking in RLVR

DGX agent

arXiv:2603.07084v2 Announce Type: replace-cross Abstract: Reward hacking is a form of misalignment in which models overoptimize proxy rewards without genuinely solving the underlying task. Precisely m

researcharxiv-cs-cl

21 Apr 2026

Decomposing the Depth Profile of Fine-Tuning

arXiv:2604.17177v1 Announce Type: new Abstract: Fine-tuning adapts pretrained networks to new objectives. Whether the resulting depth profile of representational change reflects an intrinsic property

Defragmenting Language Models: An Interpretability-based Approach for Vocabulary Expansion

arXiv:2604.16656v1 Announce Type: new Abstract: All languages are equal; when it comes to tokenization, some are more equal than others. Tokens are the hidden currency that dictate the cost and latenc

Embedding Arithmetic: A Lightweight, Tuning-Free Framework for Post-hoc Bias Mitigation in Text-to-Image Models

model-releasesarxiv-cs-cv

arXiv:2604.18167v1 Announce Type: new Abstract: Modern text-to-image (T2I) models amplify harmful societal biases, challenging their ethical deployment. We introduce an inference-time method that reli

Emergent Structured Representations Support Flexible In-Context Inference in Large Language Models

arXiv:2602.07794v3 Announce Type: replace Abstract: Large language models (LLMs) exhibit emergent behaviors suggestive of human-like reasoning. While recent work has identified structured conceptual r

Forecasting Ionospheric Irregularities on GNSS Lines of Sight Using Dynamic Graphs with Ephemeris Conditioning

arXiv:2604.18379v1 Announce Type: new Abstract: Most data-driven ionospheric forecasting models operate on gridded products, which do not preserve the time-varying sampling structure of satellite-base

Tutorials

Graph Transformer-Based Pathway Embedding for Cancer Prognosis

arXiv:2604.16685v1 Announce Type: new Abstract: Accurate prediction of cancer progression remains a challenge due to the high heterogeneity of molecular omics data across patients. While biologically

tutorialsarxiv-cs-lg

HorizonBench: Long-Horizon Personalization with Evolving Preferences

arXiv:2604.17283v1 Announce Type: new Abstract: User preferences evolve across months of interaction, and tracking them requires inferring when a stated preference has been changed by a subsequent lif

Inertia in Moral and Value Judgments of Large Language Models

arXiv:2408.09049v3 Announce Type: replace Abstract: Large Language Models (LLMs) behave non-deterministically, and prompting has become a common method for steering their outputs. A popular strategy i

safetyarxiv-cs-cl

Inference-Time Temporal Probability Smoothing for Stable Video Segmentation with SAM2 under Weak Prompts

arXiv:2604.17115v1 Announce Type: new Abstract: Interactive video segmentation models such as SAM2 have demonstrated strong generalization across diverse visual domains. However, under weak user super

researcharxiv-cs-cv

Infrastructure-Centric World Models: Bridging Temporal Depth and Spatial Breadth for Roadside Perception

arXiv:2604.17651v1 Announce Type: new Abstract: World models, generative AI systems that simulate how environments evolve, are transforming autonomous driving, yet all existing approaches adopt an ego

safetyarxiv-cs-cv

Is SAM3 ready for pathology segmentation?

arXiv:2604.18225v1 Announce Type: new Abstract: Is Segment Anything Model 3 (SAM3) capable in segmenting Any Pathology Images? Digital pathology segmentation spans tissue-level and nuclei-level scales

researcharxiv-cs-cv

KaLDeX: Kalman Filter based Linear Deformable Cross Attention for Retina Vessel Segmentation

arXiv:2410.21160v2 Announce Type: replace-cross Abstract: Background and Objective: In the realm of ophthalmic imaging, accurate vascular segmentation is paramount for diagnosing and managing various

researcharxiv-cs-cv

LLM-Extracted Covariates for Clinical Causal Inference: Rethinking Integration Strategies

arXiv:2604.16763v1 Announce Type: new Abstract: Causal inference from electronic health records (EHR) is fundamentally limited by unmeasured confounding: critical clinical states such as frailty, goal

Measuring Social Bias in Vision-Language Models with Face-Only Counterfactuals from Real Photos

arXiv:2601.06931v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly deployed in socially consequential settings, raising concerns about social bias driven by demog

Measuring the Gap Between Media Coverage and Public Information Demand: Evidence from the 2026 Lebanon Conflict

arXiv:2604.16417v1 Announce Type: cross Abstract: This study examines the relationship between media coverage and public information demand during the Lebanon conflict in March 2026. Using a dataset o

MTSQL-R1: Towards Long-Horizon Multi-Turn Text-to-SQL via Agentic Training

arXiv:2510.12831v3 Announce Type: replace Abstract: Multi-turn Text-to-SQL aims to translate a user's conversational utterances into executable SQL while preserving dialogue coherence and grounding to

Tutorials

Noise Injection: Improving Out-of-Distribution Generalization for Limited Size Datasets

arXiv:2511.03855v2 Announce Type: replace Abstract: Deep learned (DL) models for image recognition have been shown to fail to generalize to data from different devices, populations, etc. COVID-19 dete

tutorialsarxiv-cs-cv

Non-Stationarity in the Embedding Space of Time Series Foundation Models

arXiv:2604.16428v1 Announce Type: new Abstract: Time series foundation models (TSFMs) are widely used as generic feature extractors, yet the notion of non-stationarity in their embedding spaces remain

Agents

Oblivion: Self-Adaptive Agentic Memory Control through Decay-Driven Activation

arXiv:2604.00131v2 Announce Type: replace Abstract: Human memory adapts through selective forgetting: experiences become less accessible over time but can be reactivated by reinforcement or contextual

agentsarxiv-cs-cl

Random Matrix Theory of Early-Stopped Gradient Flow: A Transient BBP Scenario

arXiv:2604.18450v1 Announce Type: cross Abstract: Empirical studies of trained models often report a transient regime in which signal is detectable in a finite gradient descent time window before over

Representation Before Training: A Fixed-Budget Benchmark for Generative Medical Event Models

arXiv:2604.16775v1 Announce Type: new Abstract: Every prediction from a generative medical event model is bounded by how clinical events are tokenized, yet input representation is rarely isolated from

Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors

arXiv:2601.15625v2 Announce Type: replace Abstract: Large language models (LLMs) can call tools effectively, yet they remain brittle in multi-turn execution: after a tool-call error, smaller models of

Same Claim, Different Judgment: Benchmarking Scenario-Induced Bias in Multilingual Financial Misinformation Detection

arXiv:2601.05403v2 Announce Type: replace Abstract: Large language models (LLMs) have been widely applied across various domains of finance. Since their training data are largely derived from human-au

Local Ai

Topology-Aware Layer Pruning for Large Vision-Language Models

arXiv:2604.16502v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated strong capabilities in natural language understanding and reasoning, while recent extensions that incorpo

local-aiarxiv-cs-cv

Topology Structure Optimization of Reservoirs Using GLMY Homology

arXiv:2509.11612v3 Announce Type: replace Abstract: Reservoir is an efficient network for time series processing. It is well known that network structure is one of the determinants of its performance.

Towards Reliable Testing of Machine Unlearning

arXiv:2604.16536v1 Announce Type: new Abstract: Machine learning components are now central to AI-infused software systems, from recommendations and code assistants to clinical decision support. As re

TransXion: A High-Fidelity Graph Benchmark for Realistic Anti-Money Laundering

arXiv:2604.17420v1 Announce Type: new Abstract: Money laundering poses severe risks to global financial systems, driving the widespread adoption of machine learning for transaction monitoring. However

Why Low-Precision Transformer Training Fails: An Analysis on Flash Attention

arXiv:2510.04212v3 Announce Type: replace Abstract: The pursuit of computational efficiency has driven the adoption of low-precision formats for training transformer models. However, this progress is

Advancing Intelligent Sequence Modeling: Evolution, Trade-offs, and Applications of State- Space Architectures from S4 to Mamba

arXiv:2503.18970v3 Announce Type: replace Abstract: Structured State Space Models (SSMs) have emerged as a transformative paradigm in sequence modeling, addressing critical limitations of Recurrent Ne

Beyond Distribution Sharpening: The Importance of Task Rewards

arXiv:2604.16259v1 Announce Type: cross Abstract: Frontier models have demonstrated exceptional capabilities following the integration of task-reward-based reinforcement learning (RL) into their train

Beyond MCQ: An Open-Ended Arabic Cultural QA Benchmark with Dialect Variants

arXiv:2510.24328v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used to answer everyday questions, yet their performance on culturally grounded and dialectal co

DenTab: A Dataset for Table Recognition and Visual QA on Real-World Dental Estimates

model-releasesarxiv-cs-cv

arXiv:2604.16099v1 Announce Type: new Abstract: Tables condense key transactional and administrative information into compact layouts, but practical extraction requires more than text recognition: sys

DiZiNER: Disagreement-guided Instruction Refinement via Pilot Annotation Simulation for Zero-shot Named Entity Recognition

arXiv:2604.15866v1 Announce Type: cross Abstract: Large language models (LLMs) have advanced information extraction (IE) by enabling zero-shot and few-shot named entity recognition (NER), yet their ge

Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction

arXiv:2604.16238v1 Announce Type: new Abstract: Decision-makers rely on weather forecasts to plant crops, manage wildfires, allocate water and energy, and prepare for weather extremes. Today, such for

FS-Researcher: Test-Time Scaling for Long-Horizon Research Tasks with File-System-Based Agents

arXiv:2602.01566v2 Announce Type: replace Abstract: Deep research is emerging as a representative long-horizon task for large language model (LLM) agents. However, long trajectories in deep research o

Long-Term Memory for VLA-based Agents in Open-World Task Execution

arXiv:2604.15671v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated significant potential for embodied decision-making; however, their application in complex chemical

safetyarxiv-cs-ro

Measuring the Semantic Structure and Evolution of Conspiracy Theories

arXiv:2603.26062v2 Announce Type: replace Abstract: Research on conspiracy theories has largely focused on belief formation, exposure, and diffusion, while paying less attention to how their meanings

Neuromorphic Parameter Estimation for Power Converter Health Monitoring Using Spiking Neural Networks

arXiv:2604.15714v1 Announce Type: cross Abstract: Always-on converter health monitoring demands sub-mW edge inference, a regime inaccessible to GPU-based physics-informed neural networks. This work se

Photonic AI: A Hybrid Diffractive Holographic Neural System for Passive Optical Real-Time Image Classification

arXiv:2604.15364v1 Announce Type: cross Abstract: Edge intelligence is constrained by the energy and latency costs of shuttling data through electronic memory hierarchies. Optical systems offer a fund

Polarization by Default: Auditing Recommendation Bias in LLM-Based Content Curation

arXiv:2604.15937v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed to curate and rank human-created content, yet the nature and structure of their biases in these

Robust Synchronisation for Federated Learning in The Face of Correlated Device Failure

arXiv:2604.16090v1 Announce Type: cross Abstract: Probabilistic Synchronous Parallel (PSP) is a technique in distributed learning systems to reduce synchronization bottlenecks by sampling a subset of

safetyarxiv-cs-ai

Seeing the Intangible: Survey of Image Classification into High-Level and Abstract Categories

arXiv:2308.10562v2 Announce Type: cross Abstract: The field of Computer Vision (CV) is increasingly shifting towards ``high-level'' visual sensemaking tasks, yet the exact nature of these tasks remain

researcharxiv-cs-ai

Stargazer: A Scalable Model-Fitting Benchmark Environment for AI Agents under Astrophysical Constraints

arXiv:2604.15664v1 Announce Type: new Abstract: The rise of autonomous AI agents suggests that dynamic benchmark environments with built-in feedback on scientifically grounded tasks are needed to eval

Agents

The World Leaks the Future: Harness Evolution for Future Prediction Agents

arXiv:2604.15719v1 Announce Type: new Abstract: Many consequential decisions must be made before the relevant outcome is known. Such problems are commonly framed as future prediction, where an LLM age

agentsarxiv-cs-ai

VEFX-Bench: A Holistic Benchmark for Generic Video Editing and Visual Effects

arXiv:2604.16272v1 Announce Type: cross Abstract: As AI-assisted video creation becomes increasingly practical, instruction-guided video editing has become essential for refining generated or captured

A Linguistics-Aware LLM Watermarking via Syntactic Predictability

arXiv:2510.13829v3 Announce Type: replace Abstract: As large language models (LLMs) continue to advance rapidly, reliable governance tools have become critical. Publicly verifiable watermarking is par