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Learning with Local Search MCMC Layers

arXiv:2505.14240v3 Announce Type: replace Abstract: Integrating combinatorial optimization layers into neural networks has recently attracted significant research interest. However, many existing appr

Length-Adaptive Decoding for Masked Diffusion Machine Translation

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arXiv:2608.22274v1 Announce Type: cross Abstract: Machine translation tests masked diffusion language models (dLLMs) because every source token must be rendered faithfully, while fixed canvas decoding

model-releasesarxiv-cs-ai

25 Aug 2026

Length-Controlled Margin-Based Preference Optimization without Reference Model

model-releasesarxiv-cs-cl

arXiv:2502.14643v3 Announce Type: replace Abstract: Direct Preference Optimization (DPO) is a widely adopted offline algorithm for preference-based reinforcement learning from human feedback (RLHF), d

Let Credit Follow Computation: Architecture-Aware Credit Transport for Large Language Model Reinforcement Learning

arXiv:2608.21501v1 Announce Type: new Abstract: Credit assignment in large-language-model reinforcement learning (LLM RL) can be separated into three objects: evidence about success, a transport opera

Safety

Let the Bullets Fly: Multimodal Fake News Detection with Temporal-Aligned Generative Danmaku

arXiv:2608.22832v1 Announce Type: new Abstract: The social interactions among crowds via extit{Danmaku} (a.k.a., bullet comments) on modern multimedia platforms can facilitate both viewpoint conflicts

safetyarxiv-cs-ai

LetzCross: A Cross-Lingual Page-Level Benchmark for Multimodal Retrieval over Luxembourgish Documents

model-releasesarxiv-cs-cl

arXiv:2608.21714v1 Announce Type: new Abstract: Recent page-image retrievers such as ColPali have improved retrieval over visually rich documents, yet little is known about how they behave in cross-li

Local Ai

Leveraging Remote Traffic Data for Local Air Pollutant Estimation: A Scenario-Based Machine Learning Study Across London Monitoring Sites

arXiv:2608.23219v1 Announce Type: new Abstract: Vehicular traffic is a major source of air pollution; however, the contribution of remotely acquired traffic information to local machine-learning (ML)

local-aiarxiv-cs-lg

Lexical Coupling in GUI Element Grounding: Sentence Embeddings Track Labels across Mobile and Web

arXiv:2608.21794v1 Announce Type: cross Abstract: GUI grounding evaluations that expose UI elements as text metadata often treat high instruction-element embedding similarity as evidence of semantic g

Lexical Perturbations Disrupt LLM Reasoning: An Empirical Study of Attention Diversion

arXiv:2608.22140v1 Announce Type: cross Abstract: Large Language Models (LLMs) achieve strong reasoning performance, but their robustness to realistic lexical corruption remains poorly understood. We

Lies We Can Trust: Quantifying Action Uncertainty with Inaccurate Stochastic Dynamics through Conformalized Nonholonomic Lie groups

arXiv:2512.10294v2 Announce Type: replace Abstract: We propose Conformal Lie-group Action Prediction Sets (CLAPS), a symmetry-aware conformal prediction-based algorithm that constructs, for a given ac

researcharxiv-cs-ro

Applications

Lifelong Robot Recomposition via Persistent Categorical Modeling for Unified Task-Driven Co-Design, Verification, and Planning

arXiv:2608.21676v1 Announce Type: new Abstract: Robotic systems are traditionally designed and deployed in static configurations, with assumptions made at design-time becoming immutable constraints du

applicationsarxiv-cs-ro

Lightweight Multi-scale Hierarchical Anomaly Detection and Localization for Geospatial Big Data Applications at the Edge

arXiv:2608.22648v1 Announce Type: cross Abstract: As an increasing number of critical applications, including environmental, emergency, meteorological, and agricultural, rely on real-time anomaly dete

Tutorials

LISM: Long-range Integrative State space Models via Input-Latent State Interactions

arXiv:2509.04226v2 Announce Type: replace Abstract: State space models (SSMs) are an emerging paradigm that achieves linear-time scaling, however, they intrinsically suffer from 'curse of memory'. The

tutorialsarxiv-cs-lg

LiST: Local-Simplex Test-Time LoRA Fusion

arXiv:2608.22370v1 Announce Type: new Abstract: Task-specific LoRA adapters offer a modular way to specialize large language and vision-language models. However, existing adapter composition methods a

Hardware

LiteEvent-AE: Lightweight Autoencoder for Event-Based Vision on Low-Latency Energy-Constrained Edge Devices

arXiv:2608.21764v1 Announce Type: cross Abstract: Event-based vision has emerged as a promising paradigm for energy-aware artificial intelligence (AI), offering sparse, low-latency visual signals that

hardwarearxiv-cs-ai

Applications

LITERARYBIGFIVE: Author-Personalized Text Generation in a Unified Interpretable Space

arXiv:2608.23124v1 Announce Type: cross Abstract: Personalized text generation for authors and literary writing is essential for applications such as adaptive writing assistants, creative support tool

applicationsarxiv-cs-ai

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LitReview Arena: Evaluating Literature Review Agents with Battle-Style Peer Review Platform

arXiv:2608.21374v1 Announce Type: new Abstract: Literature reviews are essential to scientific progress, but rigorously evaluating automatically generated reviews remains difficult because many aspect

safetyarxiv-cs-ai

LLM assisted writing deserves empirical evaluation

arXiv:2608.22124v1 Announce Type: new Abstract: LLM-assisted writing is often treated as a detection problem, as it raises questions about clarity, integrity, equity, and evaluation. An analysis of 69

agentsarxiv-cs-cl

LLM-Based Adversarial Persuasion Attacks on Fact-Checking Systems

arXiv:2601.16890v2 Announce Type: replace-cross Abstract: Automated fact-checking (AFC) systems are susceptible to adversarial attacks, enabling false claims to evade detection. Existing adversarial f

LLM-based Agents for Forecasting and Prediction: Methods, Training, Evaluation, and Applications

arXiv:2608.23058v1 Announce Type: new Abstract: Large language models (LLMs) now support forecasting systems that combine language-based reasoning with temporal data, evidence retrieval, external tool

LLM-Based Selection of Incongruent Verbal and Nonverbal Behavior for Virtual Humans

arXiv:2608.22731v1 Announce Type: new Abstract: Nonverbal behavior generation systems for virtual agents often take an utterance as input and generate nonverbal behaviors that emphasize or illustrate

LLM Evaluation on Unseen Questions: Contextual Multidimensional IRT Model

arXiv:2608.22295v1 Announce Type: cross Abstract: Evaluation of large language models (LLMs) increasingly requires predicting how a model will perform on new questions or tasks before collecting large

Tutorials

LLM Pedagogical Behavior in AI Tutoring Interactions

arXiv:2608.22993v1 Announce Type: new Abstract: Students increasingly use LLMs as tutors for coursework and problem solving. Little is known about the level of assistance LLMs provide when students us

tutorialsarxiv-cs-cl

LLM-Specific Utility for Retrieval-Augmented Generation

arXiv:2510.11358v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) is typically optimized for topical relevance, yet its success ultimately depends on whether retrieved pas

LLM4LLM: Bridging Kernel Benchmarks and Real Deployment via Closed-Loop Agentic Optimization

arXiv:2608.21836v1 Announce Type: new Abstract: Large language models have become increasingly capable agents for low-level code and kernel optimization, but isolated kernel benchmarks provide only a

LLMs are Few-Shot Decision-Makers: Generalized Context-Aware Microgrid Frequency Control through Prompt Decision Transformer

arXiv:2608.21858v1 Announce Type: cross Abstract: The rapid evolution of energy structures has positioned microgrids as pivotal components of next-generation power systems, offering enhanced resilienc

LLMs for Survey Text Analysis - A Performance Comparison Between Humans and GPT-5 on Inductive Content Analysis

arXiv:2608.22417v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to support text analysis in qualitative research, yet evidence on their performance in inductive cont

Localization-Infused Vision-Language Semantic Fusion for Text-Guided Medical Image Segmentation

arXiv:2607.16327v2 Announce Type: replace Abstract: Medical image segmentation is essential for modern computer-aided medicine. Recently, text-guided segmentation has shown promise by incorporating cl

Safety

Long-Horizon Audio-Visual Generation for Persistent Stories and Interactive Worlds

arXiv:2608.23383v1 Announce Type: new Abstract: Video generation is progressing beyond isolated clips toward long-form narratives and interactive worlds, requiring models to preserve identities, follo

safetyarxiv-cs-cv

Long-term User Engagement Optimization through Model-agnostic Downstream Rewards Learning

arXiv:2607.14192v3 Announce Type: replace Abstract: As recommender systems mature in the past few years, their optimization objectives have evolved from a primary focusing on short-term behavioral sig

LongWoF-Bench: Evaluating EvoMap Genes for Verifiable Long-Workflow Tasks

model-releasesarxiv-cs-cl

arXiv:2608.23200v1 Announce Type: new Abstract: Large language models are increasingly expected to execute complex workflows whose success depends on maintaining interdependent constraints and produci

Lookahead-then-Verify: Reliable Constrained Decoding for Diffusion LLMs under Context-Free Grammars

arXiv:2602.00612v3 Announce Type: replace Abstract: Diffusion Large Language Models (dLLMs) have demonstrated promising generative capabilities and are increasingly used to produce formal languages de

researcharxiv-cs-cl

Loopy: Seamless Video Loop Generation via Anchored Looping Shift of Positional Embedding

arXiv:2608.23090v1 Announce Type: new Abstract: Looping videos are essential for practical applications such as web graphics, game development, and social media. However, existing approaches typically

Applications

Loss Landscape Features That Make Adam Stall: Definitions, Estimators, and the Preconditioned Hessian View

arXiv:2608.22145v1 Announce Type: new Abstract: Across implicit-neural-representation (INR) architectures and analytic benchmarks we observe that a thoroughly tuned Adam (especially its learning rate

applicationsarxiv-cs-lg

Loss-Parameterized Fisher Width Along Learning Trajectories

model-releasesarxiv-cs-lg

arXiv:2608.21561v1 Announce Type: new Abstract: Fisher width measures the Gaussian width of a probe set after deformation by the local Fisher geometry. We study its evolution along learning trajectori

LoViF 2026 The First Challenge on Unified Removal of Raindrops and Reflections: Methods and Results

arXiv:2608.22723v1 Announce Type: new Abstract: This workshop paper comprehensively reviews the First Challenge on Unified Removal of Raindrops and Reflections. The challenge aims to address a frequen

agentsarxiv-cs-cv

Tutorials

LpWM: A Case for Sparse Representations in World Models

arXiv:2608.22764v1 Announce Type: new Abstract: Joint-embedding predictive architectures (JEPAs) learn latent dynamics for planning and avoid representation collapse by matching features to maximum-en

tutorialsarxiv-cs-lg

Ludi{}_{scriptscriptstyle 0.1}: An Agentic System for Socially Intelligent Robots

arXiv:2608.22035v1 Announce Type: new Abstract: Robot foundation models have substantially advanced perception and control, but natural human-robot collaboration requires more than executing isolated

agentsarxiv-cs-ro

M^3ISR: A Multi-Modal Multi-View Benchmark for 3D/4D Gaussian Splatting and Feedforward Compression

arXiv:2608.22465v1 Announce Type: new Abstract: High-fidelity free-viewpoint video (FVV) and interactive rendering increasingly rely on explicit Gaussian representations, yet practical deployment rema

MACD: Multi-Agent Clinical Diagnosis with Self-Learned Knowledge for LLM

arXiv:2509.20067v5 Announce Type: replace Abstract: Large language models (LLMs) have shown promise in supporting medical diagnosis, with prompting-based methods offering a flexible and deployable mea

agentsarxiv-cs-ai

Machine Learning Assisted Inverse Design of Pixelated mmWave Patch Antennas

arXiv:2608.23469v1 Announce Type: cross Abstract: A machine learning-assisted framework for the inverse design of pixelated millimetre-wave patch antennas targeting the 22--30 GHz band is presented. T

Local Ai

Macro-Action Topological Navigation under Noisy Localization using Reinforcement Learning

arXiv:2608.23055v1 Announce Type: new Abstract: Navigating large, photorealistic 3D apartments from raw pixels is widely considered infeasible for plain reinforcement learning. We build an agent that

local-aiarxiv-cs-lg

MADE: Benchmark Environments for Closed-Loop Materials Discovery

model-releasesarxiv-cs-lg

arXiv:2601.20996v2 Announce Type: replace Abstract: Existing benchmarks for computational materials discovery primarily evaluate static predictive tasks or isolated computational sub-tasks. While valu

MADR: MPC-guided Adversarial DeepReach

arXiv:2510.18845v2 Announce Type: replace Abstract: Hamilton-Jacobi (HJ) Reachability offers a framework for generating safe value functions and policies in the face of adversarial disturbance, but is

researcharxiv-cs-ro

Magnitude Homology Is the Associated Graded of the Length Filtration

arXiv:2608.21479v1 Announce Type: cross Abstract: Magnitude homology is graded by length and knows nothing of persistence. Its persistent refinement knows nothing of where its bars begin and end. We s

Mamba-based Selective State Space Modeling Improves the Accuracy-Complexity Tradeoff of SmolVLA Vision-Language-Action Experts

arXiv:2608.21407v1 Announce Type: cross Abstract: Vision-language-action (VLA) models face a crucial tradeoff between their task success rate and the policy-call frequency. Executing a single action p

Mapping the Concept Landscape: Structural Perception of Global Distributions for Transparent Data Pruning

arXiv:2608.22858v1 Announce Type: cross Abstract: Existing data pruning methods predominantly rely on high-dimensional feature embeddings to measure sample importance. However, these compressed vector

researcharxiv-cs-cv

MASH-Bench: Diagnosing Cross-Source Failure in Mass-Shooting Risk Classification

model-releasesarxiv-cs-lg

arXiv:2608.22460v1 Announce Type: new Abstract: Public mass-shooting databases differ substantially in coverage, feature availability, and reporting practices, creating challenges for machine-learning