Search: “model-releases”

From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMs

arXiv:2506.13182v3 Announce Type: replace-cross Abstract: [...] Since then, various APR approaches, especially those leveraging the power of large language models (LLMs), have been rapidly developed t

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Model Releases

From Gradient-Boosted Trees to Deep Recommenders: Practical Lessons from Migrating a Production Customer Support Recommender

DGX agent

arXiv:2608.24132v1 Announce Type: cross Abstract: Product catalogs in fast-moving service businesses are shifting from static, independently priced SKUs toward dynamically bundled, discount-coupled of

model-releasesarxiv-cs-ai

26 Aug 2026

From Relaxed Indexability to Exact Indexability: A t-Step Approach for Partially Observable Restless Bandits

arXiv:2608.24167v1 Announce Type: new Abstract: Whittle index policies offer a scalable method for restless multi-armed bandits, but under partial observability even determining the indifference subsi

Gated Activation Steering for Reducing Sycophancy & Hallucination in Medical Question Answering

arXiv:2608.23666v1 Announce Type: new Abstract: Sycophancy and hallucination are persistent failure modes of Large Language Models (LLMs) across domains. However, it becomes particularly consequential

GATNextHop: A GAT for Shortest Path Routing with Cross-Topology Generalization

arXiv:2608.23917v1 Announce Type: new Abstract: Common shortest-path algorithms, such as Dijkstra's (SPF), that OSPF uses, provide exact routing solutions but must be recomputed for each network topol

'Ghaib in Translation' aka Unseen Harm: Measuring Cross-Script Safety Inconsistency with 'Missed-in-Urdu' Scores in LLM Hate Speech Detection

arXiv:2608.24191v1 Announce Type: cross Abstract: Urdu, the world's tenth most spoken language with 246 million speakers, remains almost entirely absent from mainstream LLM safety evaluation and nine

GlanceWAM: Sparse Test-Time Imagination for World-Action Models

arXiv:2608.23927v1 Announce Type: new Abstract: Video generative models provide rich physical priors for robot learning, yet existing world-action models (WAMs) face a fundamental trade-off: synchrono

Gripper-aware Vision Language Action Models

model-releasesarxiv-cs-ro

arXiv:2608.24603v1 Announce Type: new Abstract: Vision language action models (VLAs) have advanced general purpose robotic grasping and manipulation by enabling robots to interpret visual observations

Hierarchical Skill Retrieval for Data-Efficient Adaptation of Vision-Language-Action Models

arXiv:2608.24042v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models pretrained on large-scale robot datasets provide a strong foundation for robot manipulation, their performan

HiQA: A Hierarchical Contextual Augmentation RAG for Multi-Documents QA

arXiv:2402.01767v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) significantly improves document-based question answering by integrating external documents during generat

HMGCLIP: Heterogeneous Multi-Granularity Contrastive Learning for E-commerce Representation Learning

arXiv:2608.24467v1 Announce Type: new Abstract: Although recent Multimodal Large Language Models (MLLMs) have advanced general product understanding, they implicitly encode product information into gl

Hybrid Semantic Tool Discovery for Enterprise MCP Gateway: Architecture and Implementation

arXiv:2608.23992v1 Announce Type: cross Abstract: Large language model (LLM) agents invoke external tools to retrieve and reason over information beyond pretrained knowledge. The Model Context Protoco

ICA: Information-Aware Credit Assignment for Visually Grounded Long-Horizon Information-Seeking Agents

arXiv:2602.10863v2 Announce Type: replace-cross Abstract: Long-horizon reinforcement learning for information seeking agents remains difficult because terminal rewards reveal whether the final answer

Identifying Latent Declarative Representations of Code for Assisting Repository Migration

arXiv:2608.23619v1 Announce Type: cross Abstract: Legacy software repositories embed decades of domain knowledge in undocumented code, making understanding and modernization difficult. We treat a prog

Latent Action as Intention Enables Efficient Future Imagination for World Action Models

model-releasesarxiv-cs-ro

arXiv:2608.24882v1 Announce Type: new Abstract: World action models (WAMs) improve robot control by modeling how observations evolve, but generating future observations at test time incurs substantial

LG-GER: Language-Guided Group Emotion Recognition via Multimodal Evidence Distillation

arXiv:2608.23880v1 Announce Type: new Abstract: Inferring the collective emotional state of a group of people from a single image, a task known as group emotion recognition (GER), requires integrating

Life-Bench: A Benchmark and Knowledge Graph Framework for Multimodal Personalization Beyond Concept Recognition

arXiv:2602.19001v2 Announce Type: replace Abstract: As large language models increasingly power personal assistants, users expect them to reason over multimodal life histories, from recognizing people

LLM Agents Perform Controlled Experiments Using Simulation Models

arXiv:2608.23622v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong capabilities in reasoning, planning, and tool use, but many scientific and engineering tasks require more

Low-Rank Ternary Adaptation for Fine-Tuning Transformers

arXiv:2608.24469v1 Announce Type: new Abstract: Ternary transformers offer extreme memory and compute efficiency, but existing low-bit LoRA-based methods cannot directly fine-tune ternary weights. Cur

Luce: Relightable Gaussians for 3D Asset Generation

arXiv:2608.23943v1 Announce Type: cross Abstract: High-fidelity image-to-3D generation requires a 3D representation that captures both geometry and appearance. To support relighting and integration in

Mahalanobis-Based Multi-Head Attention for Complex State Propagation

arXiv:2608.24462v1 Announce Type: new Abstract: In this paper, we propose extbf{Mahalanobis-Based Multi-Head Attention} (MHA-CSP), a novel attention mechanism that replaces the standard dot-product wi

MARS: Multi-Specialist LLM Relay System for Competitive Programming

arXiv:2608.23918v1 Announce Type: new Abstract: Large Language Models excel at code generation, yet competitive programming exposes a persistent failure mode: existing multi-agent pipelines distribute

Massive-STEPS: Massive Semantic Trajectories for Understanding POI Check-ins -- Dataset and Benchmarks

arXiv:2505.11239v4 Announce Type: replace Abstract: Understanding human mobility through Point-of-Interest (POI) trajectory modeling is increasingly important for applications such as urban planning,

MatReplace: A Reference-Free, Conditioning-Aligned Benchmark for Material Replacement in Interior Scenes

arXiv:2608.24107v1 Announce Type: cross Abstract: Material replacement is a common interior-design operation: changing the material of a selected surface while preserving its geometry, surroundings, a

Meta^n: Recursive Self-Improvement through Emergent Depth

arXiv:2608.24735v1 Announce Type: new Abstract: Self-improving LLM agents refine answers, not the process that produces those answers. Systems that add a meta-level hold that level fixed, and those th

Mind the Student: Behavioral and Contextual Cues for Automated Engagement Prediction in Online Learning

arXiv:2608.24340v1 Announce Type: cross Abstract: The prediction of student engagement from the online tutoring videos is difficult because engagement is a multidimensional construct comprising distin

(Mis)Understanding Benign Overfitting in Equity Return Prediction

arXiv:2608.23761v1 Announce Type: cross Abstract: Highly overparameterized models often predict well despite interpolating training data in complex domains, challenging the classical bias--variance tr

Model Effect or Label Effect? Refined Annotations and a Human-Referenced Benchmark for Pulmonary Embolism Segmentation

arXiv:2608.24486v1 Announce Type: cross Abstract: Purpose: To quantify how evaluation annotations influence measured pulmonary embolism (PE) segmentation performance relative to model training changes

MoE-based Feature Adapter for Prompt-free Binary Coronary Artery Segmentation in X-ray Angiography

arXiv:2608.24783v1 Announce Type: new Abstract: Accurate segmentation of coronary arteries in X-ray angiography videos is essential for quantitative coronary analysis and image-guided interventions. H

MolEmb: Multimodal Large Language Models Can Be Strong Molecular Embedding Models

arXiv:2608.23646v1 Announce Type: new Abstract: Molecular embedding models can serve as foundational infrastructure for computational chemistry and drug discovery, where reusable vector representation

More GPUs or a Smaller Cache? Tensor Parallelism versus KV Compression for Memory-Bound LLM Serving

arXiv:2608.23962v1 Announce Type: new Abstract: When an LLM serving deployment runs out of KVcache room, there are two well-established ways out. Tensor parallelism shards the weights and the KV cache

MoRF-AST: Calibrated Probabilistic Virtual Sensing for Structural Monitoring under Changing Operating Conditions

arXiv:2608.24531v1 Announce Type: cross Abstract: Probabilistic full-field reconstruction provides uncertainty-aware response evidence for structural reliability assessment, yet inference from sparse

MPIB: A Benchmark for Medical Prompt Injection Attacks and Clinical Safety in LLMs

arXiv:2602.06268v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems are increasingly integrated into clinical workflows. However, pr

Neurosymbolic Alignment for Physiologically-Safe Clinical Language Models

arXiv:2608.24534v1 Announce Type: new Abstract: Clinical LLMs can generate recommendations that are factually plausible yet physiologically unsafe. We investigate whether safety alignment can be impro

Object Counting Across Modalities: Taxonomies, Benchmarks, Applications, and Open Challenges

arXiv:2608.23845v1 Announce Type: new Abstract: Object-counting methods have rapidly shifted from class-specific density regression to open-vocabulary, foundation-model-backed counters. These methods

Olapa-MCoT: Enhancing the Chinese Mathematical Reasoning Capability of LLMs

arXiv:2312.17535v2 Announce Type: replace Abstract: In the past two years, the outstanding performance of ChatGPT in multilingual and multitasking has led to large language models (LLMs) attracting wi

OmniJudge or OmniBias? Diagnosing Multimodal Judges through Balanced, Decoupled Lenses

arXiv:2608.24160v1 Announce Type: new Abstract: Multimodal understanding models that can jointly judge text-to-image (T2I), text-to-video (T2V) and text-to-speech (TTS) generation are increasingly use

ORBITALIF: An Efficient Spiking Federated Learning Framework for Onboard Cloud Removal

arXiv:2608.24073v1 Announce Type: cross Abstract: Low-earth-orbit (LEO) satellites enable high-resolution, large-scale Earth observation for applications such as disaster monitoring and environmental

Parameter-Efficient Self-Supervised Adaptation for EEG-FM under Fixed Computational Budgets

arXiv:2608.24727v1 Announce Type: cross Abstract: EEG foundation models pretrained via self-supervised learning promise transferable representations, but their generalization remains limited, especial

Parameter-Level Attribution of Symmetry in Trained Networks Though Parameter-Wise Functional Sensitivity

arXiv:2608.24700v1 Announce Type: new Abstract: When a network has learned a function with a known symmetry, can that symmetry be moved through the parametrisation---is there a motion in parameter spa

Parameterized Complexity of L_p-Lipschitz Constants for Input Convex Neural Networks and L_p-Norm Maximization over Zonotopes

arXiv:2608.24865v1 Announce Type: cross Abstract: Lipschitz constants are a standard way to quantify the sensitivity of neural networks to small input perturbations, but computing them is difficult ev

Parason: Revealing Subtask and Trial Parallelism in LLM Reasoning

arXiv:2608.24658v1 Announce Type: new Abstract: Scaling test-time reasoning has substantially improved the problem-solving ability of large language models (LLMs), but standard autoregressive decoding

Paritok-4B: Intent-Conditioned Context Compression for Coding Agents

arXiv:2608.24188v1 Announce Type: new Abstract: Coding agents re-send large file reads and tool outputs to a frontier LLM every turn, and this context dominates their token bill. General-purpose promp

PeakBench: Benchmarking Resource-Aware Tool Invocation in LLM Agents

arXiv:2608.24509v1 Announce Type: new Abstract: LLM agents increasingly solve tasks by invoking multiple tools, where parallel execution is essential for low latency but difficult to manage safely. Ex

Physics-Integrated Operator Learning via Gaussian Splatting Representations

arXiv:2608.24049v1 Announce Type: new Abstract: Neural operators provide efficient surrogates for spatiotemporal PDE systems, but purely data-driven formulations often accumulate substantial errors du

PhysicsBench: A Unified Leaderboard for Generative and Predictive Models in Engineering Design and Simulation

arXiv:2608.24056v1 Announce Type: new Abstract: Generative and predictive artificial intelligence models are increasingly used to generate geometry and to predict physical fields and scalar quantities

Pipeline-Native Transformers: Co-Designing Model Architecture and CPU Inference for Bandwidth-Efficient Autoregressive Decode

arXiv:2608.23841v1 Announce Type: cross Abstract: Single-token autoregressive decode on CPUs is bound by memory bandwidth, not arithmetic: a modern CPU sustains roughly 1 TFLOP/s of compute but only a

Pivot-and-Station Multi-Agent Path Finding: Solvability, Complexity, and Algorithms

arXiv:2608.24585v1 Announce Type: new Abstract: Automated high-density storage systems (warehouses, robotic parking, plant logistics, etc.) require fleets of agents to move through scarce task-critica