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arXiv:2605.29765v1 Announce Type: new Abstract: We introduce MMTM, a modular pipeline for topic discovery in long-form video that integrates speech recognition, audio and visual embeddings, and BERTop

researcharxiv-cs-lg

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Research

MVP-Shapley: Feature-based Modeling for Evaluating the Most Valuable Player in Basketball

DGX agent

arXiv:2506.04602v4 Announce Type: replace-cross Abstract: The burgeoning growth of the esports and multiplayer online gaming community has highlighted the critical importance of evaluating the Most Va

researcharxiv-cs-lg

29 May 2026

Permutation-Invariant Spectral Learning via Dyson Diffusion

arXiv:2510.08535v2 Announce Type: replace-cross Abstract: Diffusion models are central to generative modeling and have been adapted to graphs by diffusing adjacency matrix representations. The challen

Realistic honeypot evaluations for scheming propensity

arXiv:2605.29729v1 Announce Type: new Abstract: We introduce scheming honeypot evaluations, a framework for testing whether models will pursue instrumental goals if given the opportunity. Our scheming

ReasonLight: A Multimodal Foundation Model-Enhanced Reinforcement Learning Framework for Zero-Shot Traffic Signal Control

arXiv:2605.29425v1 Announce Type: new Abstract: Reinforcement learning (RL) has shown promise in traffic signal control (TSC). However, its reliance on predefined states limits responsiveness to obser

safetyarxiv-cs-ai

SAHG: Sector-Anisotropic Hyperbolic Graph Model for Social Bot Detection

arXiv:2605.30166v1 Announce Type: cross Abstract: LLM-driven social bots can generate fluent, human-like text, reducing the discriminative advantage of content-based detection alone. However, coordina

SigmaMedStat: Temporal Signal Modeling for ICU False Alarm Reduction

arXiv:2605.29236v1 Announce Type: new Abstract: Alarm fatigue in intensive care units (ICUs) is a well documented patient safety crisis. Clinical monitors generate 350 or more alarms per patient per d

Small Agent Group is the Future of Digital Health

arXiv:2602.08013v2 Announce Type: replace Abstract: The rapid adoption of large language models (LLMs) in digital health has been driven by a 'scaling-first' philosophy, i.e., the assumption that clin

The Trust Paradox: How CS Researchers Engage LLM Leaderboards

arXiv:2605.28966v1 Announce Type: new Abstract: Large language model (LLM) leaderboards rank AI models using standardized benchmarks and have become highly visible across computer science, despite kno

AdaDPO: Self-Adaptive Direct Preference Optimization with Balanced Gradient Updates

arXiv:2605.28440v1 Announce Type: new Abstract: DPO has become a widely adopted alternative to RLHF for aligning LLMs with human preferences, eliminating the need for a separate reward model or RL loo

Research

Applications of temporal graph learning for predicting the dynamics of biological systems

arXiv:2605.28659v1 Announce Type: new Abstract: Biological foundation models have shown strong performance in single-cell representation learning by applying transformer architectures directly to gene

researcharxiv-cs-lg

DebFilter: Eradicating Biases Stashed in Value

arXiv:2605.28167v1 Announce Type: new Abstract: Text-to-image diffusion models, which are theoretically equivalent to score-based generative models, generate images through a multi-step denoising proc

safetyarxiv-cs-cv

FPMoE: A Sparse Mixture-of-Experts Approach to Functional Code Generation

arXiv:2605.27849v1 Announce Type: cross Abstract: Despite rapid progress in LLM-based code generation, existing models are predominantly trained on imperative languages, leaving functional programming

Heterogeneous Multi-Agent Modeling for Measurement and Network Analysis of the Data Service Market

arXiv:2605.27433v1 Announce Type: cross Abstract: With the increasing complexity of collaboration among various social entities and user demands, the factors affecting the stable development of the da

agentsarxiv-cs-ai

KVoiceBench, KOpenAudioBench, and KMMAU: Agent-Driven Korean Speech Benchmarks for Evaluating SpeechLMs

arXiv:2605.27984v1 Announce Type: cross Abstract: Speech language models (SpeechLMs) have achieved substantial progress by extending large language models (LLMs) to the speech modality. However, Speec

Mathematical Modelling of Ethical AI Use in Higher Education: A Coordination Game Framework for Future-Facing Learning

arXiv:2605.27400v1 Announce Type: cross Abstract: The rapid uptake of generative artificial intelligence (AI) in higher education is reshaping assessment practices and intensifying concerns around aca

safetyarxiv-cs-ai

Applications

Measuring Massive Multitask Chinese Understanding

arXiv:2304.12986v3 Announce Type: replace-cross Abstract: The development of large-scale Chinese language models is flourishing, yet there is a lack of corresponding capability assessments. Therefore,

applicationsarxiv-cs-ai

MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation

arXiv:2605.28035v1 Announce Type: new Abstract: In recent years, Multi-Talker Audio-Video Generation (MTAVG) models have shown promising performance on fundamental metrics such as lip-sync and audio-v

Multi-Adapter Representation Interventions via Energy Calibration

arXiv:2605.28722v1 Announce Type: new Abstract: Representation intervention has emerged as a promising paradigm for aligning large language models toward desired behaviors without modifying model weig

MUSE: Benchmarking Manufacturable, Functional, and Assemblable Text-to-CAD Generation

arXiv:2605.28579v1 Announce Type: new Abstract: Large language models (LLMs) have recently advanced text-driven 3D generation, yet Text-to-CAD remains far from supporting industrial product design. Ex

The Alignment Floor: When Persona Customization Is Safe

arXiv:2605.27382v1 Announce Type: cross Abstract: A key promise of pluralistic AI is behavioral adaptation: persona prompts like 'be creative' or 'be thorough' let systems respect diverse user values

TRACES: Proactive Safety Auditing for Multi-Turn LLM Agents via Trajectory-State Modeling

arXiv:2605.27690v1 Announce Type: new Abstract: LLM agents increasingly operate through multi-turn tool use and environment interaction, where safety risks often emerge from intermediate steps long be

safetyarxiv-cs-cl

ADRD-Bench: A Preliminary LLM Benchmark for Alzheimer's Disease and Related Dementias

arXiv:2602.11460v2 Announce Type: replace Abstract: Large language models (LLMs) have shown great potential for healthcare applications. However, existing evaluation benchmarks provide minimal coverag

Benchmark Leakage Trap: Can We Trust LLM-based Recommendation?

arXiv:2602.13626v3 Announce Type: replace Abstract: The expanding integration of Large Language Models (LLMs) into recommender systems poses critical challenges to evaluation reliability. This paper i

Constraint acquisition needs better benchmarks

arXiv:2605.26279v1 Announce Type: new Abstract: Constraint Acquisition (CA) and related research on the validation and enhancement of Mathematical Programming (MP) models from domain knowledge artifac

DunbaaBERT: From Sacrifice to Semantics

arXiv:2605.26935v1 Announce Type: new Abstract: Large language models have achieved strong performance across many NLP tasks, yet Urdu remains comparatively underexplored due to limited resources and

EmoDistill: Offline Emotion Skill Distillation for Language Model Agents in Adversarial Negotiation

arXiv:2605.26785v1 Announce Type: cross Abstract: Post-trained LLMs are often optimized to align responses with human preferences, making them safe, polite, and conversationally appropriate. In advers

safetyarxiv-cs-ai

Geometry-Aware Representation Denoising for Robust Multi-view 3D Reconstruction

model-releasesarxiv-cs-cv

arXiv:2605.26230v1 Announce Type: new Abstract: Multi-view 3D reconstruction has achieved remarkable progress with the advent of feed-forward 3D reconstruction models. However, these models are typica

MTL-FNO: A Lightweight Multi-Task Fourier Neural Operator for Sparse Field Reconstruction

arXiv:2605.26718v1 Announce Type: new Abstract: Efficient onboard multi-field sparse reconstruction is essential for the autonomous operation of aerospace vehicles. While existing deep learning models

Prompt Injection Detection is Regime-Dependent: A Deployment-Aware Evaluation with Interpretable Structural Signals

arXiv:2605.26999v1 Announce Type: new Abstract: Prompt injection poses a critical threat to the safe deployment of large language models, yet existing detection approaches are typically evaluated unde

Stability Implies Redundancy: Delta Attention Selective Halting for Efficient Long-Context Prefilling

arXiv:2604.18103v2 Announce Type: replace Abstract: Prefilling computational costs pose a significant bottleneck for Large Language Models (LLMs) and Large Multimodal Models (LMMs) in long-context set

The Bridge-Garden Dilemma in LLM Distillation: Why Mixing Hard and Soft Labels Works

arXiv:2605.26246v1 Announce Type: new Abstract: Knowledge distillation (KD) transfers knowledge from a large teacher model to a smaller student. In language modeling, the student is trained either on

When Does LeJEPA Learn a World Model?

arXiv:2605.26379v1 Announce Type: cross Abstract: A representation that scrambles the true degrees of freedom of the world cannot support reliable planning or compositional generalization. We prove th

When LLMs Benchmark Themselves: Deconstructing Self-Bias in Automated Evaluation

arXiv:2509.26600v2 Announce Type: replace-cross Abstract: As LLMs rapidly saturate existing benchmarks, automated benchmark creation using LLMs (LLM-as-a-benchmark) -- where a model generates test inp

Act or Clarify? Modeling Sensitivity to Uncertainty and Cost in Communication

arXiv:2602.02843v3 Announce Type: replace Abstract: When deciding how to act under uncertainty, agents may choose to act to reduce uncertainty or they may act despite that uncertainty. In communicativ

agentsarxiv-cs-cl

An Efficient Learning Method to Connect Observables

arXiv:2503.01684v3 Announce Type: replace-cross Abstract: Constructing fast and accurate surrogate models is a key ingredient for making robust predictions in many topics. We introduce a new model, th

Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction

arXiv:2605.24657v1 Announce Type: new Abstract: Major LLM platforms deploy models in an inference-only configuration: the model serves requests but never updates per-user weights. Users must repeatedl

Applications

Beyond Static Uncertainty: Modeling Temporal Uncertainty Dynamics for Probabilistic Time Series Forecasting

arXiv:2603.24254v2 Announce Type: replace-cross Abstract: Real-world time series exhibit temporally structured uncertainty: volatility clusters in turbulent regimes, dissipates in stable periods, and

applicationsarxiv-cs-ai

Beyond the Target: From Imitation to Collaboration in Speculative Decoding

arXiv:2605.24793v1 Announce Type: new Abstract: Speculative decoding (SPD) accelerates large language model (LLM) inference by letting a smaller draft model propose multiple future tokens that are ver

safetyarxiv-cs-cl

Research

DRIVE: Modeling Skills at the Reasoning and Interaction Levels for Web Agents under Continual Learning

arXiv:2605.23939v1 Announce Type: new Abstract: Web agents require both high-level reasoning (for task decomposition) and low-level interactions (for page elements manipulation) to conduct different t

researcharxiv-cs-ai

Empirical Analysis and Detection of Hallucinations in LLM-Generated Bug Report Summaries

arXiv:2605.24137v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to generate summaries of software bug reports, including sections such as Steps-to-Reproduce (S2R),

Improving the Completeness and Comparability of Segment Disclosures: A Large Language Model Approach

arXiv:2605.23924v1 Announce Type: new Abstract: Segment-level disclosures are a central component of financial reporting, providing insight into firms' internal organization and the allocation of econ

safetyarxiv-cs-cl

Applications

Missing Pattern Recognized Diffusion Imputation Model for Missing Not At Random

arXiv:2605.25439v1 Announce Type: new Abstract: Missing data frequently arises across diverse domains, including time-series and image domains. In the real world, missing occurrences often depend on t

applicationsarxiv-cs-lg

Tutorials

Mode-as-Sequence: Translating Multimodal Motion Prediction into Unified Sequential Mode Modeling

arXiv:2605.24037v1 Announce Type: cross Abstract: Multimodal motion forecasting is inherently under-supervised: each training scene provides only one realized future, yet multiple plausible futures ex

tutorialsarxiv-cs-ai

Optimal Design for Multinomial Logit Model with Applications to Best Assortment Identification

arXiv:2605.25592v1 Announce Type: cross Abstract: We study optimal experimental design for multinomial logit (MNL) bandits, where an agent repeatedly selects a subset of K items from a ground set of s

agentsarxiv-cs-lg

Palette: A Modular, Controllable, and Efficient Framework for On-demand Authorized Safety Alignment Relaxation in LLMs

arXiv:2605.24154v1 Announce Type: new Abstract: Current safety alignment of foundation models largely follows a one-size-fits-all paradigm, applying the same refusal policy across users and contexts.

PCGRLLM: Large Language Model-Driven Reward Design for Procedural Content Generation Reinforcement Learning

arXiv:2502.10906v2 Announce Type: replace Abstract: Reward design plays a pivotal role in the training of game AIs, requiring substantial domain-specific knowledge and human effort. In recent years, s

agentsarxiv-cs-ai

SLAP: Stratified Loss-based Pruning for On-Policy Data-Efficient Instruction Tuning

arXiv:2605.23969v1 Announce Type: new Abstract: Instruction tuning has optimized the specialized capabilities of large language models (LLMs), but it often requires extensive datasets and prolonged tr