Search: “models”

From Arithmetic to Logic: The Resilience of Logic and Lookup-Based Neural Networks Under Parameter Bit-Flips

arXiv:2603.22770v2 Announce Type: replace-cross Abstract: The deployment of deep neural networks (DNNs) in safety-critical edge environments necessitates robustness against hardware-induced bit-flip e

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From Judgments to Issues: Structured Extraction of Legal Reasoning with Citation-Hallucination Control

DGX agent

arXiv:2607.03325v1 Announce Type: cross Abstract: We present an automated pipeline that decomposes Italian tax-court judgments into individual legal issues and extracts, for each issue, a structured X

model-releasesarxiv-cs-ai

7 Jul 2026

Full Glyph Images Beat Token Embeddings: A Controlled Study for Transformers

arXiv:2607.03994v1 Announce Type: cross Abstract: Modern language models generally represent text as sequences of discrete token embeddings, an assumption deeply rooted in current practice but rarely

GenShin: Guiding Rational Liposome Design by Ranking Liposomal Protein Corona through a Docking-Pose-Free GNN

arXiv:2504.13853v2 Announce Type: replace-cross Abstract: Rational design of lipid nanoparticles (LNPs) for tissue-specific delivery critically depends on predicting the composition of the protein cor

Graph Neural Networks for the Graphical Bootstrap

arXiv:2607.03109v1 Announce Type: cross Abstract: We study a graph classification problem involving over 20 million graphs, arising from high-order perturbative computations of correlators in planar N

Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction

arXiv:2607.04912v1 Announce Type: cross Abstract: In patients with breast cancer, pathological complete response (pCR) has been established as a clinically meaningful surrogate marker for long-term ou

HAS-Bench: Evaluating LLM-Based Human-Agent Systems under Configurable Human Participation

arXiv:2607.04329v1 Announce Type: new Abstract: Large language models increasingly operate in settings where humans are active collaborators rather than passive task providers. We introduce HAS-Framew

High-Precision Formation Control for Heterogeneous Multi-Robot Systems via Hierarchical Hybrid Physics-Informed Deep Reinforcement Learning

arXiv:2607.03512v1 Announce Type: new Abstract: Existing classical control methods commonly require precise models and struggle to cope with model uncertainties and external disturbances, while end-to

safetyarxiv-cs-ro

How Many Iterations to Jailbreak? Dynamic Budget Allocation for Multi-Turn LLM Evaluation

arXiv:2605.06605v2 Announce Type: replace Abstract: Evaluating and predicting the performance of large language models (LLMs) in multi-turn conversational settings is critical yet computationally expe

Improving LLMs via Validator-to-Generator Alignment

arXiv:2607.02668v1 Announce Type: new Abstract: Large language models are inconsistent: varying prompts or including unrelated information can lead to unexpected changes in model outputs. The generato

safetyarxiv-cs-cl

Iterative Visual Thinking and the Self-Correction Mirage in VLM Grounding

arXiv:2606.13156v2 Announce Type: replace-cross Abstract: Letting a vision-language model (VLM) think longer at test time has driven much recent progress. A natural way to bring this to spatial ground

safetyarxiv-cs-ai

Last-Meter Precision Navigation for UAVs: A Diffusion-Refined Aerial Visual Servoing Approach

arXiv:2607.04352v1 Announce Type: new Abstract: In this work, we study the last-meter precision navigation for UAVs, e.g., autonomously reaching a target within the final 10 meters using monocular vis

Learning to Generate Multiple Objects from Dense and Occluded Layouts

arXiv:2607.03488v1 Announce Type: new Abstract: Text-to-image diffusion models fail to generate correct object counts in dense scenes, where overlapping instances collapse into indistinguishable struc

Longitudinal-Motion-Aware Lateral Control for Autonomous Vehicles: A Robust Nonlinear Control Framework

model-releasesarxiv-cs-ro

arXiv:2607.02924v1 Announce Type: new Abstract: As autonomous vehicles (AVs) operate in increasingly dynamic traffic conditions, lateral control must be performed while longitudinal speed and accelera

MedCalc-Pro: Solving Complex Medical Calculations with LLM Agents

arXiv:2607.02879v1 Announce Type: new Abstract: Current benchmarks for evaluating large language models (LLMs) in medical calculation are largely based on simplified settings, where each patient case

Medi-Gemma: A Hybrid Clinical Decision Support System Integrating Deterministic EMR Analytics and Retrieval-Augmented Generation

arXiv:2607.04907v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in high-stakes clinical settings remains limited by structural hallucinations, weak deterministic reasoning over

Local Ai

MedMambaLite: Hardware-Aware Mamba for Medical Image Classification

arXiv:2508.05049v1 Announce Type: cross Abstract: AI-powered medical devices have driven the need for real-time, on-device inference such as biomedical image classification. Deployment of deep learnin

local-aiarxiv-cs-cv

Memory-Efficient FastText: A Comprehensive Approach Using Double-Array Trie Structures and Mark-Compact Memory Management

model-releasesarxiv-cs-cl

arXiv:2506.01254v2 Announce Type: replace Abstract: FastText remains a practical choice for industrial word representation because it can synthesize vectors for out-of-vocabulary words from character

Motion Attribution for Video Generation

arXiv:2601.08828v2 Announce Type: replace-cross Abstract: Despite the rapid progress of video generation models, the role of data in influencing motion is poorly understood. We present Motive (MOTIon

Nonparametric Control Koopman Operators

arXiv:2405.07312v5 Announce Type: replace-cross Abstract: This paper presents a novel Koopman composition operator representation framework for control systems in reproducing kernel Hilbert spaces (RK

NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO

arXiv:2607.03957v1 Announce Type: cross Abstract: Language models can reach the right normative verdict for the wrong reason. We introduce NormWorlds-CF, a solver-verified environment for counterfactu

OmniLayout: A Schematic-Coupled Multimodal Benchmark for Constraint-Aware Geometric Reasoning in PCB Layout

arXiv:2607.03261v1 Announce Type: new Abstract: Recent large language models (LLMs) have demonstrated remarkable progress in 3D spatial reasoning, spatial grounding, and fine-grained geometric underst

Open-Weather Robust 3D Detection via Dual-Critic Diffusion Alignment

arXiv:2607.01983v1 Announce Type: cross Abstract: Robust 3D object detection under adverse weather remains a critical hurdle for autonomous driving. Despite progress with LiDAR-4D radar fusion, most m

PAGE: Towards Practical Human-level Gaze Target Estimation

arXiv:2607.04860v1 Announce Type: new Abstract: Gaze target estimation, the task of predicting where a person is looking in a scene, is crucial to understanding human attention and intent. It is a cha

researcharxiv-cs-cv

ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution

arXiv:2603.02510v2 Announce Type: replace Abstract: The transition from sequential to parallel computing is essential for modern high-performance applications but is hindered by the steep learning cur

PDFBench: A Benchmark for De novo Protein Design from Function

arXiv:2505.20346v3 Announce Type: replace-cross Abstract: Function-guided protein design is a crucial task with significant applications in drug discovery and enzyme engineering. However, the field la

PPE-Bench: A Benchmark for Evaluating MLLM Unlearning under Private-Public Entanglement

arXiv:2607.02897v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have shown strong capabilities, but they may memorize private information from web data, raising privacy conc

Probing Geospatial SSL Representations with Environmental Signals

arXiv:2607.05207v1 Announce Type: new Abstract: Self-supervised learning (SSL) is designed to learn generic, transferable representations rather than representations optimized for a single task. Most

Quantize the Target, Quantize the Drafter: Efficient Inference with Qwen3.5-4B

arXiv:2607.04244v1 Announce Type: new Abstract: This report describes our approach to the Efficient Qwen Competition, where the goal is to enable low-latency serving of Qwen3.5-4B on a resource-constr

Reading Between the Dots: Decoding Hidden Computation across Filler Tokens

arXiv:2607.03502v1 Announce Type: cross Abstract: Frontier LLMs can perform multi-step reasoning over content-free filler tokens like dots or counting sequences, producing correct answers with no visi

ReLo-IRR: Reflection-Guided LoRA Framework for Image Reflection Removal

arXiv:2607.02957v1 Announce Type: new Abstract: Single-image reflection removal (SIRR) aims to recover the clean transmission layer from a reflection-contaminated image. Although recent methods achiev

Risk-Constrained Freshness-Aware Semantic Caching for Open-Web Retrieval-Augmented LLMs

arXiv:2607.04281v1 Announce Type: cross Abstract: Semantic caching reduces the latency and cost of retrieval-augmented generation (RAG) by serving cached answers to semantically similar queries, but m

SABLE: An NDA-Safe Closed-Loop LLM Framework for Analog Circuit Optimization in Industrial EDA Flows

arXiv:2607.03701v1 Announce Type: cross Abstract: Large language models (LLMs) can propose circuit-optimization decisions, but industrial analog flows cannot expose foundry PDK content, proprietary sc

safetyarxiv-cs-lg

Serious Games: Human-AI Interaction, Evolution, and Coevolution

arXiv:2505.16388v2 Announce Type: replace Abstract: The serious games between humans and AI have only just begun. Evolutionary Game Theory (EGT) models the competitive and cooperative strategies of bi

Shapley-based Data Valuation for LLM Alignment via Sequential Preference Optimization

arXiv:2512.15765v3 Announce Type: replace Abstract: Data valuation is a natural framework for understanding which preference datasets matter most when aligning a Large Language Model (LLM) using multi

safetyarxiv-cs-lg

Shifting from Discrete to Continuous Reference Data: QSM-Derived Horizontal Tree Biomass Distribution for Deep Learning Biomass Estimation

arXiv:2607.05260v1 Announce Type: cross Abstract: Conventional modeling approaches for LiDAR-based above-ground biomass (AGB) estimation rely on discrete plot-level inventory aggregates. This methodol

Applications

Shortcut Learning in Legal Judgment Prediction: Empirical Evidence from the UK Employment Tribunal

arXiv:2607.04261v1 Announce Type: new Abstract: Current Legal Judgment Prediction (LJP) is constrained by its reliance on post-hoc judicial materials, increasing the likelihood that models perform ret

applicationsarxiv-cs-ai

SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses

arXiv:2510.15476v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used as interfaces to information, code, and real-world services, making prompt-level security f

safetyarxiv-cs-ai

Agents

The Changing Role of Symbolic Methods in Artificial Intelligence

arXiv:2607.05168v1 Announce Type: new Abstract: Why do intelligent systems need to perform explicit symbolic reasoning? Computer science has traditionally regarded symbolic reasoning as a defining com

agentsarxiv-cs-ai

Toward Efficient Agents: Memory, Tool learning, and Planning

arXiv:2601.14192v2 Announce Type: replace Abstract: Recent years have witnessed increasing interest in extending large language models into agentic systems. While the effectiveness of agents has conti

Unsupervised Features Mining via Activation Geometry

arXiv:2607.04222v1 Announce Type: new Abstract: Interpretability methods aim to reveal the features represented inside large language models (LLMs). Many existing methods begin with labeled examples o

AbsoluteDegradation: A Physics-Inspired Synthetic Film-Degradation Pipeline and Archival Film Restoration Benchmark

arXiv:2607.02131v1 Announce Type: cross Abstract: Restoring archival film remains a fundamentally challenging problem due to the absence of paired training data and the lack of standardized evaluation

Activation Steering for Aligned Open-ended Generation without Sacrificing Coherence

arXiv:2604.08169v2 Announce Type: replace Abstract: Alignment in LLMs is more brittle than commonly assumed: misalignment can be induced by adversarial prompts, benign fine-tuning, emergent misalignme

Composite Reward Design in PPO-Driven Adaptive Filtering

arXiv:2506.06323v2 Announce Type: replace-cross Abstract: Model-free and reinforcement learning-based adaptive filtering methods are gaining traction for denoising in dynamic, non-stationary environme

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair

arXiv:2607.01916v1 Announce Type: new Abstract: Large language model agents can repair real repository issues, but they often spend large context budgets on whole-file reads, broad searches, and long

Denser neq Better: Limits of On-Policy Self-Distillation for Continual Post-Training

model-releasesarxiv-cs-cl

arXiv:2607.01763v1 Announce Type: cross Abstract: Continual post-training enables foundation models to acquire new knowledge while preserving existing capabilities. Recent work suggests that on-policy

Do Newer Lightweight CNNs Perform Better Under Resource Constraints? A Controlled Multigenerational Study of Architecture, Initialization, Training Budget, and Efficiency

arXiv:2607.01984v1 Announce Type: cross Abstract: Newer lightweight convolutional neural networks are often presented as improving predictive performance and deployment efficiency, but such claims req

EPnG: Adaptive Expert Prune-and-Grow for Parameter-Efficient MoE Fine-tuning

arXiv:2607.01789v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models scale efficiently but remain costly to adapt due to redundant experts and uniform parameter allocation. Existing param