Search: “models”

EnergyBridge: Benchmarking Household Energy Management, User Participation, and Grid Flexibility

arXiv:2608.08691v1 Announce Type: new Abstract: Residential virtual power plants (VPPs) can provide grid flexibility by shifting household demand, but physical flexibility becomes dependable capacity

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Model Releases

Entropy-based Code Adversarial Translation for Real-world Repository Migration

DGX agent

arXiv:2608.09273v1 Announce Type: new Abstract: LLMs have demonstrated strong capabilities in code generation and automated program repair, but migrating an entire repository rarely produces a runnabl

model-releasesarxiv-cs-ai

11 Aug 2026

Exact Contraction Rates via the Berkson--Porta Representation: A Sharp Threshold and Its Herglotz-Kernel Obstruction

model-releasesarxiv-cs-ro

arXiv:2608.07552v1 Announce Type: cross Abstract: Semigroups of holomorphic self-maps of the unit disc with an interior fixed point are, by the classical Berkson--Porta representation, entirely determ

Applications

Exploring LLM Capabilities for Situational Understanding and COLREG compliance on real-world maritime navigation scenarios

arXiv:2608.08281v1 Announce Type: new Abstract: Recently, Large Language Models (LLMs) have shown considerable capability for situational understanding, reasoning, and decision making in different dom

applicationsarxiv-cs-ai

Failure-Mechanism Transferability of Cumulative-Damage Features for Health State Estimation of SiC Power Modules

arXiv:2608.08365v1 Announce Type: cross Abstract: Data-driven health-state estimators for SiC (Silica-Carbide) power modules typically report their performance on a single accelerated-aging campaign,

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 in

Findings of the First Teaching Monster Challenge: A Benchmark of Pedagogical Content Knowledge in AI Agents

arXiv:2608.08852v1 Announce Type: new Abstract: AI agents can now solve problems, answer like subject experts, and generate long-form multimodal content. However, whether they can adapt a lesson to fi

Finite Constant Frontiers and Auditable Regret Certificates for Average-Reward Reinforcement Learning

arXiv:2608.07725v1 Announce Type: new Abstract: Average-reward reinforcement-learning regret is known up to logarithmic factors, but the numerical content of published guarantees is difficult to compa

Floating-Point Neural Network Verification at the Software Level

arXiv:2510.23389v2 Announce Type: replace-cross Abstract: The behaviour of neural network components must be proven correct before deployment in safety-critical systems. Unfortunately, existing neural

Forgotten History or Test-of-Time? Retrospect and Prospect on RAG from an IR Perspective

arXiv:2608.08445v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) is widely regarded as a novel paradigm born from the limitations of large language models (LLMs)--a mechanism to gr

From Product Search to Preference Articulation: The Economics of Agentic Commerce

arXiv:2608.08395v1 Announce Type: cross Abstract: Generative AI is shifting digital commerce from browsing toward agentic search, in which consumers delegate product discovery to AI agents. We compare

From Recovery to Drop-off: How Action Post-training Reduces a VLM's Late-Layer Depth Decodability

arXiv:2608.08904v1 Announce Type: cross Abstract: How much of a vision-language model's (VLM) spatial understanding remains after the action post-training process of building a vision-language-action

From token probabilities to calibrated confidence: An empirical study of mathematical question answering

arXiv:2608.07827v1 Announce Type: cross Abstract: Confidence estimation for large language models (LLMs) aims to estimate the probability that a generated answer is correct, while calibration aligns t

researcharxiv-cs-cl

FSTC-Encoder: Feature--Spatial--Temporal Correlation Learning for Generalizable RF Sensing

arXiv:2608.08439v1 Announce Type: cross Abstract: Heterogeneous RF sensing differs substantially in feature structure, spatial layout, and temporal scale, making existing models difficult to reuse acr

Goose: Anisotropic Speculation Trees for Training-Free Speculative Decoding

arXiv:2604.02047v2 Announce Type: replace-cross Abstract: Speculative decoding accelerates large language model inference by drafting multiple candidate tokens and verifying them in a single forward p

GraphThink: Graph-Enhanced LLM Thinking for Long-Horizon Embodied Task Planning

arXiv:2608.07905v1 Announce Type: new Abstract: Embodied agents using LLM-based planners often struggle with physical hallucinations, poor generalization to long-horizon tasks, and lack of environment

HeatCast: A Benchmark for Neighborhood-Scale LST Forecasting across 124 U.S. Cities

arXiv:2608.07640v1 Announce Type: new Abstract: Land Surface Temperature (LST) is a widely used satellite-derived measure of urban surface heat, but there is no shared benchmark for forecasting it at

High Fidelity Capture, Reconstruction, and Transfer of Human Demonstrations for Robot-Assisted Bathing

model-releasesarxiv-cs-ro

arXiv:2608.09127v1 Announce Type: new Abstract: Despite the demand for robots in high-value clinical tasks like bathing, contemporary systems still lack the safety and reliability required for complex

How Much Backtracking is Enough? Exploring the Interplay of SFT and RL in Enhancing LLM Reasoning

arXiv:2505.24273v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) suggest that reinforcement learning (RL) effectively internalizes search strategies, yielding si

Imaginative Generative AI: Crossing the Entropy Wall into Worlds Beyond Imitation

arXiv:2608.09385v1 Announce Type: cross Abstract: Generative AI models are primarily designed to imitate the data distribution, an objective that neither corrects diversity lost by a learned generator

Implicit Virtual Leader: Decentralized Vision-Only Relative Pose Estimation for Multi-Robot Formations

model-releasesarxiv-cs-ro

arXiv:2607.15708v2 Announce Type: replace Abstract: Classical leader-follower formation control suffers from single points of failure and error propagation, and relies on absolute localization sensors

Improving Generalization Robustness of Multimodal RLVR

arXiv:2608.08802v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) makes Multimodal Large Language Models more accurate, but the gains are brittle: simply paraphrasi

Instruction Set and Language for Hypergraphs

arXiv:2607.10194v2 Announce Type: replace-cross Abstract: We present IsalHG, a method for representing the structure of any finite, connected hypergraph of bounded hyperedge arity as a string over a c

Is the ACL Responsible NLP Checklist a Box-Ticking Exercise? A Large-Scale Analysis of EMNLP 2025

model-releasesarxiv-cs-cl

arXiv:2608.09280v1 Announce Type: new Abstract: Responsible NLP practice includes a) transparency, b) ethics, and c) societal impacts. The Responsible NLP Checklist aims to push these goals, and promo

Agents

Keep It Simple: Multi-Key Episodic Memory Retrieval for Ultra-Long Video Understanding

arXiv:2608.07663v1 Announce Type: cross Abstract: When videos extend from hours to days, directly processing them end-to-end becomes impractical for current Multi-modal Large Language Models (MLLMs).

agentsarxiv-cs-ai

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. Typical machine learning screening methods require PD labels, but the ava

Learning from Consensus and Disagreement: Unsupervised On-Policy Self-Distillation with Minority-Trajectory Contrast

arXiv:2608.08764v1 Announce Type: cross Abstract: On-policy self-distillation improves language-model reasoning by querying a teacher on states actually visited by the student. Recent methods create a

Learning Structural Illumination for Unsupervised Low-light Enhancement

arXiv:2608.08153v1 Announce Type: new Abstract: Existing unsupervised low-light image enhancement (LLIE) methods often estimate illumination directly from the entire low-light input, without separatin

Learning to Coordinate Symbolic Tools: LLM Agents for Verified Sum-of-Squares Certificates

arXiv:2608.00326v2 Announce Type: replace Abstract: Tool calling allows large language models (LLMs) to invoke external computation during problem solving, a useful capability in various fields includ

LGNNIC: Acceleration of Large-Scale GNN Training using SmartNICs

arXiv:2608.07733v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are widely used across domains such as natural sciences, social network analysis, chip design, and recommendation systems

LIBAD: A Multimodal Anomaly Detection Benchmark for Li-Ion Battery Electrode Manufacturing

arXiv:2608.07958v1 Announce Type: new Abstract: Multimodal industrial anomaly detection has largely focused on discrete products using strongly correlated RGB and 3D observations, leaving continuous p

LibraSpec: Dynamic Diffusion-Based Speculative Decoding via Marginal-Gain-Driven Optimization

arXiv:2608.08721v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by drafting multiple tokens for parallel verification, with efficiency critically dete

LLM-Guided Heuristic Design from Simulation Traces: A Case Study in Dynamic Production and AGV Scheduling

arXiv:2608.09343v1 Announce Type: new Abstract: Simulation-based optimization (SBO) evaluates executable policies under stochastic dynamics, but most methods treat the simulator as a black box: aggreg

Agents

M^3Prune: Hierarchical Communication Graph Pruning for Efficient Multi-Modal Multi-Agent Retrieval-Augmented Generation

arXiv:2511.19969v2 Announce Type: replace Abstract: Recent advancements in multi-modal retrieval-augmented generation (mRAG), which enhance multi-modal large language models (MLLMs) with external know

agentsarxiv-cs-ai

'Many Are My Names': The Anatomy of the Assistant and Its Personas via Sparse Autoencoders

arXiv:2608.07852v1 Announce Type: new Abstract: How a language model internally represents who is speaking, the Assistant, an assigned roleplay persona, or a narrated story character, remains underexp

researcharxiv-cs-cl

MELLON - Multimodal Enhanced LLM for Online Navigation

arXiv:2608.09121v1 Announce Type: new Abstract: Web navigation agents are capable of addressing various types of tasks on different websites. Current baselines on web navigation are either unimodal or

Memory-Efficient Activation Checkpointing with Sliding Window and Hirschberg's Algorithm for 0/1 Knapsack Solving in PyTorch

arXiv:2608.08740v1 Announce Type: new Abstract: Activation checkpointing minimizes the runtime of neural networks under a given memory budget, by selecting which intermediate tensors to store and whic

Hardware

Mesh-Attention: A New Communication-Efficient Distributed Attention with Improved Data Locality

arXiv:2512.20968v2 Announce Type: replace-cross Abstract: Distributed attention is essential for scaling large language models (LLMs) to long contexts, yet existing methods either have limited paralle

hardwarearxiv-cs-ai

Applications

Metadata Reconstruction from Values Alone: Recovering Column Semantics in Undocumented Warehouses

arXiv:2608.07946v1 Announce Type: cross Abstract: Text-to-SQL benchmarks ship schemas whose column names already say what the columns mean. Production warehouses are the inverse: cryptic identifiers,

applicationsarxiv-cs-ai

MetaSpace: Metamorphic Testing for Spatial Cognition in Embodied Agents

arXiv:2608.07533v1 Announce Type: new Abstract: An embodied agent is an intelligent entity that interacts with its environment through a physical body. Currently, the evaluation of embodied agents pri

Mind the Hook: Source-Level Auditing of Privacy Defenses in Retrieval-Augmented Generation

arXiv:2608.09001v1 Announce Type: cross Abstract: Black-box privacy scores for retrieval-augmented generation (RAG) are difficult to interpret unless the audited defense's active pipeline hook is know

MPISuperRes-PnP: A Super-Resolution Zero-Shot Plug-and-Play Reconstruction Algorithm for Magnetic Particle Imaging

arXiv:2608.09672v1 Announce Type: new Abstract: Magnetic Particle Imaging (MPI) is an emerging medical imaging modality. MPI is based on the non-linear response of magnetic nanoparticles to an applied

Local Ai

Multimodal Federated Learning under Dual-Axis Modality Missingness

arXiv:2608.09240v1 Announce Type: cross Abstract: Multimodal federated learning (FL) supports collaborative modeling in privacy-sensitive health-sensing and medical settings, but realistic deployments

local-aiarxiv-cs-ai

NBA_Streaming: A Large-Scale Benchmark for Fine-Grained Basketball Commentary Generation in Continuous Streams

arXiv:2608.09200v1 Announce Type: new Abstract: Live basketball commentary generation requires determining when an event is sufficiently observable and describing it before subsequent events unfold. H

NeuroGuard: Neural Gradient Update Aware of Representation Damage

arXiv:2608.08068v1 Announce Type: new Abstract: Long-tailed class-incremental learning (LT-CIL) must learn new classes from imbalanced streams while retaining old classes. Existing methods mainly chan

NewtonGS: Physics-Structured Object-Level Neural Newtonian Dynamics for Gaussian Scene Animation

arXiv:2608.07598v1 Announce Type: new Abstract: Animating objects in a static 3D Gaussian scene requires an explicit object-level dynamic state and a controllable model of object motion. Existing dyna

researcharxiv-cs-cv

No Unique Minimizer, No Problem: On the Consistency of Robust Neural Classifiers

arXiv:2608.08489v1 Announce Type: new Abstract: Neural network classifiers trained by cross-entropy minimization are highly sensitive to label noise and adversarial contamination. While robust alterna

Open-World Hierarchical Perception: Taxonomic Abstraction over Class-Agnostic Proposals for the Safe Handling of Out-of-Vocabulary Road Objects

arXiv:2608.07577v1 Announce Type: cross Abstract: A closed-set detector for autonomous driving must assign every object one of a fixed set of labels. On an object outside that set (a horse-drawn carri