arXiv AI
Aug 11
Learning an Interior Layout Policy in a Domain Specific Language Action Space
arXiv:2608. 07547v1 Announce Type: cross Abstract: Indoor scene layout generation is a challenging task in interior design.
Large language models
Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
arXiv AI
Aug 11
Weather- and Location-Aware Agentic Dining Recommendation: Leveraging LLM World Knowledge for Region-Sensitive Contextual Reasoning
arXiv:2608. 07593v1 Announce Type: cross Abstract: Context-aware recommender systems have long recognized that factors such as location, time, and weather shape where and what people choose to eat.
arXiv AI
Aug 11
Fair on the Surface? Benchmarking Hidden-Output Fairness Gaps in LLM Recommenders
arXiv:2608. 08284v1 Announce Type: new Abstract: Fairness audits for LLM-based recommenders have largely focused on observable outputs, implicitly assuming that stable recommendations reflect stable internal processing.
arXiv AI
Aug 11
Theory-Guided Deception Detection: A RAG-Based Artificial Intelligence Exploration
arXiv:2608. 08881v1 Announce Type: new Abstract: The current work developed seven Retrieval-Augmented Generation (RAG) models based on leading deception theories and compared how deception judgments were made relative to baseline models.
arXiv AI
Aug 11
LAUDE: LLM-Assisted Unit Test Generation and Debugging of Hardware DEsigns
arXiv:2601. 08856v3 Announce Type: replace-cross Abstract: Unit tests are critical in the hardware design lifecycle to ensure that component design modules are functionally correct and conform to the specification before they are integrated at the system level.
arXiv AI
Aug 11
Who Verifies the Benchmark? Decentralizing Trust in Large Language Model Evaluation
arXiv:2608. 07762v1 Announce Type: new Abstract: LLM benchmarks can build an organization's reputation and attract customers, but only when results are transparent and verifiable.
arXiv AI
Aug 11
Deferred Audio Pruning with Local Audio-Visual Dynamics for Omni-LLMs
arXiv:2608. 08794v1 Announce Type: new Abstract: Omni-modal LLMs jointly process audio, video, and text, but long multimodal sequences incur substantial prefill and KV-cache costs.
arXiv AI
Aug 11
One Adapter Pair per Model: A Universal Activation Interface for Language Models
arXiv:2608. 09521v1 Announce Type: new Abstract: Activation-based tools are usually tied to one model's native hidden space, requiring probes, sparse autoencoders, and natural-language interpreters to be rebuilt or rediscovered for each new language model.
arXiv AI
Aug 11
MoNo: Multiscale Optimal Transport Neural Operator for Solving PDEs on General Geometries
arXiv:2608. 09764v1 Announce Type: cross Abstract: Transformer-based neural operators have achieved substantial progress in solving Partial Differential Equations (PDEs) by projecting spatial observations into compact latent tokens and learning physical interactions in latent spaces.
arXiv AI
Aug 11
ACEvo: Adversarial Co-Evolution of Problem Distributions and Solvers for Combinatorial Optimization
arXiv:2506. 02594v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to synthesize heuristic programs, yet most existing pipelines optimize solvers against fixed benchmark distributions.
arXiv AI
Aug 11
ZetaGPT: A Reference Implementation of Positional--Encoding--Free State--Space--Attention Language Models
arXiv:2608. 09432v1 Announce Type: cross Abstract: Transformer-based language models rely on self-attention, whose computation is permutation-equivariant and therefore lacks an intrinsic mechanism for representing token order.
arXiv AI
Aug 11
Embedding Trust: Semantic Isotropy Predicts Nonfactuality in Long-Form Text Generation
arXiv:2510. 21891v2 Announce Type: replace-cross Abstract: To deploy large language models (LLMs) in high-stakes application domains that require substantively accurate responses to open-ended prompts, we need reliable, computationally inexpensive methods that assess the trustworthiness of long-form responses generated by LLMs.
arXiv AI
Aug 11
CRUISE: Vision-Language Model-Guided Uncertainty-Aware Cross-Modal Sensor Fusion for Robust Autonomous Driving
arXiv:2608. 09202v1 Announce Type: new Abstract: Modern autonomous vehicles are equipped with multiple sensors, such as cameras, LiDAR, and radar, for comprehensive environmental perception.
arXiv Machine Learning
Aug 11
SAGE: SLO-Aware Adaptive Retrieval for Production RAG Systems
arXiv:2608. 08237v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems in production operate under strict service level objectives (SLOs) on tail latency and infrastructure cost.
arXiv AI
Aug 11
Signature-Guided Capacity Occupancy for Dense Expert Merging
arXiv:2608. 09201v1 Announce Type: new Abstract: Dense expert merging combines domain-specialized language models into one single checkpoint, typically by admitting task-vector support in weight space.
arXiv AI
Aug 11
From Sweep to Seam: Interleaved Cross-Block Post-Training Quantization
arXiv:2608. 09595v1 Announce Type: new Abstract: Compressing large language models to two bits or fewer is increasingly feasible through block-wise post-training quantization; cross-block variants reconstruct neighboring Transformer blocks within a moving window.
arXiv Machine Learning
Aug 11
Efficient Test-Time Scaling for LLM-based Time Series Forecasting
arXiv:2608. 08675v1 Announce Type: new Abstract: Long-term time series forecasting benefits from preserving global structure such as trends and seasonality.
arXiv Machine Learning
Aug 11
Label-Free Parkinson's Disease Screening from Face and Voice through Mechanistic Interpretability
arXiv:2608. 08976v1 Announce Type: new Abstract: Parkinson's disease (PD) is the second most common neurodegenerative disorder.
arXiv AI
Aug 11
LEGO-Puzzles: How Good Are MLLMs at Multi-Step Spatial Reasoning?
arXiv:2503. 19990v4 Announce Type: replace Abstract: Many real-world applications of spatial intelligence, such as robotic control, autonomous driving, and automated assembly, require spatial reasoning across multiple sequential steps.
arXiv AI
Aug 11
From Relevance to Execution Utility: Reward-Aware Dynamic Execution Gating for Skill-Based LLM Agents
arXiv:2608. 09168v1 Announce Type: new Abstract: Agent skills are increasingly used to equip large language model (LLM) agents with reusable procedural knowledge.