Search: “context”

Supportive Token Revealing for Fast Diffusion Language Model Decoding

arXiv:2606.04236v1 Announce Type: cross Abstract: Discrete diffusion language models can generate text efficiently by updating multiple masked positions in parallel, but this parallelism introduces a

researcharxiv-cs-ai

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Temporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents

DGX agent

arXiv:2606.04555v1 Announce Type: cross Abstract: Long-horizon conversational agents need to interact with users through evolving events, tasks, and goals. Such histories are naturally temporal, yet m

local-aiarxiv-cs-ai

4 Jun 2026

The Invisible Lottery: How Subtle Cues Steer Algorithm Choice in LLM Code Generation

arXiv:2606.04057v1 Announce Type: cross Abstract: Large language models (LLMs) now generate substantial production code, often for tasks with multiple valid algorithmic solutions. Incidental prompt cu

Uncovering Insights of Compound Flooding with Data-Driven AI

arXiv:2506.04281v2 Announce Type: replace Abstract: Compound flooding, driven by nonlinear interactions between multiple hydrometeorological factors, poses a significant challenge to hazard prevention

researcharxiv-cs-lg

Unpredictable Safety: Domain-Dependent Compliance and the Transparency Gap in Open-Weight LLMs

arXiv:2606.04035v1 Announce Type: cross Abstract: We present a systematic study of domain-dependent safety behavior in open-weight LLMs: 7 standardized experiments across 7 ethical domains, testing 5

Why Muon Outperforms Adam: A Curvature Perspective

arXiv:2606.04662v1 Announce Type: cross Abstract: Muon improves training efficiency over Adam in large language-model training by about two times, but the local geometric source of this advantage rema

local-aiarxiv-cs-ai

X4Val: Learning Neural Surrogates for Variance-Reduced Policy Evaluation

arXiv:2606.05159v1 Announce Type: new Abstract: Rigorous evaluation of learning-based robotic systems is an essential prerequisite for deployment. However, real-world test data is expensive to gather;

safetyarxiv-cs-ro

A 3D Isovist World Model -- Revealing a City's Unseen Geometry and Its Emergent Cross-City Signature

model-releasesarxiv-cs-lg

arXiv:2606.03609v1 Announce Type: cross Abstract: Embodied agents that navigate cities rely on world models that predict how their surroundings will change as they move. But for navigation, what matte

A cross-domain tropical species dataset with Chinese vernacular names and CITES source links

arXiv:2606.03156v1 Announce Type: new Abstract: We describe a versioned cross-domain dataset of 410,499 active tropical species (working snapshot 2026-04-20) spanning three applied subdomains -- tropi

researcharxiv-cs-cl

A New Framework for Cybersecurity Refusals in AI Agents

arXiv:2606.02644v1 Announce Type: cross Abstract: Agentic scaffolds have dramatically improved LLM performance on complex, long-horizon tasks, yielding both broad benefits and amplified risks in domai

AAD-1: Asymmetric Adversarial Distillation for One-Step Autoregressive Video Generation

arXiv:2606.03972v1 Announce Type: new Abstract: We present AAD-1, an Asymmetric Adversarial Distillation framework for One-step autoregressive image-to-video generation. State-of-the-art methods adopt

AdaWeather: Adaptively Mixing Probabilistic Weather Forecasts with Logarithmic Regret

arXiv:2606.02663v1 Announce Type: cross Abstract: Recent advances in machine learning have produced probabilistic weather forecasting models comparable to state-of-the-art numerical weather predictors

researcharxiv-cs-ai

An Improved Method for Personalizing Diffusion Models

arXiv:2407.05312v2 Announce Type: replace Abstract: Diffusion models have demonstrated impressive image generation capabilities. Personalized approaches, such as textual inversion and Dreambooth, enha

ArrowFlow: Hierarchical Machine Learning in the Space of Permutations

model-releasesarxiv-cs-lg

arXiv:2604.04087v2 Announce Type: replace Abstract: We introduce ArrowFlow, a machine learning architecture that operates entirely in the space of permutations. Its computational units are ranking fil

Applications

AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking

arXiv:2606.03347v1 Announce Type: cross Abstract: Score-based diffusion models have emerged as prominent deep generative models; however, their application to tabular data remains challenging because

applicationsarxiv-cs-ai

Best of Both Worlds: Multimodal Reasoning and Generation via Unified Discrete Flow Matching

arXiv:2602.12221v2 Announce Type: replace Abstract: We propose UniDFlow, a unified discrete flow-matching framework for multimodal understanding, generation, and editing. It decouples understanding an

safetyarxiv-cs-cv

Bridging Predictive Uncertainty and Safe Action: Sample-Conditioned Differentiable Planning for Autonomous Driving

arXiv:2606.03296v1 Announce Type: new Abstract: Complex, dynamic, and interactive driving environments pose significant challenges for autonomous driving, primarily due to the pervasive uncertainty of

safetyarxiv-cs-ro

Coherence Maximization Improves Pluralistic Alignment

arXiv:2606.03110v1 Announce Type: new Abstract: Aligning AI systems with diverse human values requires value specifications grounded in concrete examples, but generating such examples without extensiv

safetyarxiv-cs-cl

Collab-REC: An LLM-based Agentic Framework for Balancing Recommendations in Tourism

arXiv:2508.15030v5 Announce Type: replace Abstract: We propose COLLAB-REC, a multi-agent framework designed to counteract popularity bias and improve diversity in tourism recommendations. In our setup

CoMPAS3D: A Dataset and Benchmark for Interactive Motion

arXiv:2507.19684v2 Announce Type: replace-cross Abstract: Socially interactive humanoid robots must engage with humans through their bodies, adapting in real time to a partner's movement, intent, and

Cost-Aware Query Routing in RAG: Empirical Analysis of Retrieval Depth Tradeoffs

arXiv:2606.02581v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) faces a fundamental three-way tension: deeper retrieval improves factual grounding but inflates token costs and e

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

Diagnosing Knowledge Gaps in LLM Tool Use: An Agentic Benchmark for Novel API Acquisition

arXiv:2606.03657v1 Announce Type: new Abstract: Large language models for code generation often need to use APIs that are absent from their pretraining data. This requires more than recalling a functi

Diagnosis of Human Object Interaction Detectors for Real World Educational Applications

model-releasesarxiv-cs-cv

arXiv:2606.02789v1 Announce Type: new Abstract: Human-object interaction (HOI) recognition is critical for automatically analyzing student behavior in complex educational environments. Although state-

DMF: A Deterministic Memory Framework for Conversational AI Agents

arXiv:2606.03463v1 Announce Type: new Abstract: Conversational AI agents require memory systems that are both scalable and semantically coherent across long interaction horizons. Existing approaches r

Applications

Does Language Shift Break Medical Vision-Language Models? Indonesian Radiology Visual Question Answering Case Study

arXiv:2606.03693v1 Announce Type: new Abstract: Medical Vision-Language Models (VLMs) are typically evaluated on English radiology visual question answering benchmarks, leaving their robustness under

applicationsarxiv-cs-cl

DRAN: A Distribution and Relation Adaptive Network for Spatio-temporal Forecasting

arXiv:2504.01531v4 Announce Type: replace Abstract: Accurate predictions of spatio-temporal systems are crucial for tasks such as system management, control, and crisis prevention. However, the inhere

researcharxiv-cs-lg

Evaluating Transformer and LSTM Frameworks for Prediction in Ungauged Basins

arXiv:2606.02791v1 Announce Type: new Abstract: Watershed networks exhibit convergent topologies in which multiple tributaries merge into downstream channels,integrating diverse upstream hydrological

Experience-Driven Dynamic Exits for LLMs with Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2606.03113v1 Announce Type: new Abstract: Large Language Models suffer from slow autoregressive inference. While self-speculative decoding accelerates this process, its efficiency is hampered by

extsc{CR-Seg}: Attention-Guided and CoT-Enhanced Coarse-to-Refined Reasoning Segmentation

arXiv:2606.03564v1 Announce Type: cross Abstract: Reasoning segmentation aims to segment target objects described by complex language through joint visual-textual reasoning. Existing methods typically

local-aiarxiv-cs-ai

FlashMLA-ETAP: Efficient Transpose Attention Pipeline for Accelerating MLA Inference on NVIDIA H20 GPUs

arXiv:2506.01969v3 Announce Type: replace-cross Abstract: Efficient inference of Multi-Head Latent Attention (MLA) is challenged by deploying the DeepSeek-R1 671B model on a single Multi-GPU server. T

From None to All: Self-Supervised 3D Reconstruction via Novel View Synthesis

arXiv:2603.27455v2 Announce Type: replace Abstract: In this paper, we introduce NAS3R, a self-supervised feed-forward framework that jointly learns explicit 3D geometry and camera parameters with no g

GeoSem-WAM: Geometry- and Semantic-Aware World Action Models

arXiv:2606.03188v1 Announce Type: new Abstract: Recent World Action Models (WAMs) have demonstrated impressive capabilities in embodied decision-making. However, whether their effectiveness stems from

researcharxiv-cs-ro

Graph Mamba Survival Analysis Based on Topology-Aware ordering

arXiv:2606.02602v1 Announce Type: cross Abstract: In computational pathology, Whole Slide Images (WSIs) survival analysis is crucial for patient prognosis assessment, but it faces multiple technical c

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

Agents

Handoff Debt: The Rediscovery Cost When Coding Agents Take Over Interrupted Tasks

arXiv:2606.02875v1 Announce Type: new Abstract: Coding-agent benchmarks evaluate whether a single uninterrupted agent can resolve a repository issue. Real software work is messier: tasks are interrupt

agentsarxiv-cs-ai

'Important You should give me full credits!': Exploring Prompt Injection Attacks on LLM-Based Automatic Grading Systems

arXiv:2606.03090v1 Announce Type: cross Abstract: The emergence of large language models (LLMs) has significantly accelerated recent research on LLM-based automatic grading (AG) systems. Benefiting fr

InftyThink+: Effective and Efficient Infinite-Horizon Reasoning via Reinforcement Learning

arXiv:2602.06960v3 Announce Type: replace-cross Abstract: Large reasoning models achieve strong performance by scaling inference-time chain-of-thought, but this paradigm suffers from quadratic cost, c

Language Bias under Conflicting Information in Multilingual LLMs

model-releasesarxiv-cs-cl

arXiv:2604.07123v2 Announce Type: replace Abstract: Large Language Models (LLMs) have been shown to contain biases in the process of integrating conflicting information when answering questions. Here

LAP: An Agent-to-Instrument Protocol for Autonomous Science

arXiv:2606.03755v1 Announce Type: new Abstract: Autonomous science is moving from demonstration to infrastructure. Large language model agents now plan experiments, and self-driving laboratories execu

Letting Tutor Personas Speak Up for LLMs: Learning Steering Vectors from Dialogue via Preference Optimization

arXiv:2602.07639v2 Announce Type: replace Abstract: With the emergence of large language models (LLMs) as a powerful class of generative artificial intelligence (AI), their use in tutoring has become

safetyarxiv-cs-cl

Leveraging BART to Assess CS1 C++ Programming Assignments using Rubric-based Criteria

arXiv:2606.03814v1 Announce Type: new Abstract: This paper investigates rubric-aware, multitask fine-tuning of transformer models for automated grading of introductory C++ programming assignments, wit

Lingo_Research_Group at SemEval-2026 Task 9: Evaluating Prompt Variants for Polarization Detection

arXiv:2606.03334v1 Announce Type: new Abstract: Our submission presented in this paper is for SemEval-2026 Task 9: Multilingual Text Classification Challenge - Polarization Detection and it covers all

researcharxiv-cs-cl

LiveBand: Live Accompaniment Generation in the Audio Domain

arXiv:2606.03803v1 Announce Type: cross Abstract: We present LiveBand, a real-time system that generates high-fidelity music accompaniments to live audio input, respecting strict causal constraints. O

Localized, High-resolution Geographic Representations with Slepian Functions

arXiv:2602.00392v2 Announce Type: replace Abstract: Geographic data is fundamentally local. Disease outbreaks cluster in population centers, ecological patterns emerge along coastlines, and economic a

safetyarxiv-cs-lg

LoCAtion: Long-time Collaborative Attention Framework for High Dynamic Range Video Reconstruction

arXiv:2603.14377v2 Announce Type: replace Abstract: Prevailing High Dynamic Range (HDR) video reconstruction methods are fundamentally trapped in a fragile alignment-and-fusion paradigm. While explici

safetyarxiv-cs-cv

Applications

Making Embodied AI Reliable: A Community Agenda from Testing to Formal Verification

arXiv:2606.03593v1 Announce Type: cross Abstract: Embodied AI systems are increasingly deployed in open-world environments, yet ensuring their reliability remains a fundamental challenge. Drawing on d

applicationsarxiv-cs-ro

MemVerse: Multimodal Memory for Lifelong Learning Agents

arXiv:2512.03627v2 Announce Type: replace Abstract: Despite rapid progress in large-scale language and vision models, AI agents still suffer from a fundamental limitation: they cannot remember. Withou

researcharxiv-cs-ai