Search: “models”

Diagnosing and Mitigating Retrieval Bottlenecks in LLM-Based Cold-Start Recommendation

arXiv:2606.29947v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as rerankers in recommender systems, with the expectation that semantic understanding will help in

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DialogPII: A multilingual dataset of synthetic dialog transcripts to detect personal information

DGX agent

arXiv:2606.30312v1 Announce Type: new Abstract: Conversational data collected in domains such as healthcare or social sciences is a valuable resource for research and automated analysis. However, resp

model-releasesarxiv-cs-cl

30 Jun 2026

Does Verbose Chain-of-Thought Really Help? In-Distribution Evidence that Content, Not Length, Matters

arXiv:2606.30128v1 Announce Type: new Abstract: Chain-of-thought (CoT) prompting improves LLM reasoning, but the source is contested: do the intermediate steps help because they carry useful semantic

Early Warning Signals for OpenVLA Failure under Visual Distribution Shift

arXiv:2606.29699v1 Announce Type: cross Abstract: Vision Language Action models combine perception, language grounding, and control in a single policy, but their failures are hard to diagnose once vis

Efficient Unlearning with Privacy Guarantees

arXiv:2507.04771v2 Announce Type: replace-cross Abstract: Privacy protection laws, such as the GDPR, grant individuals the right to request the forgetting of their personal data not only from database

researcharxiv-cs-lg

Ensemble Learning Based Classification Algorithm Recommendation

arXiv:2101.05993v2 Announce Type: replace-cross Abstract: Selecting an appropriate classification algorithm for a given data set remains a challenging problem in data mining and machine learning. Exis

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions

arXiv:2507.05257v4 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while a

Expert Evaluation of Clinical AI Tools on Real Point-of-Care Clinical Queries

arXiv:2606.28960v1 Announce Type: new Abstract: Physicians now pose millions of clinical questions to AI tools each week, yet these tools are evaluated largely on hypothetical or exam-style questions,

Forensic Trajectory Signatures for Agent Memory Poisoning Detection

arXiv:2606.30566v1 Announce Type: cross Abstract: We discover a behavioral invariant in LLM agents under persistent memory poisoning: in architectures where routing information is retrieved through ob

Geometrically Principled Randomized Optimization for Efficient LLM Training

arXiv:2510.01878v2 Announce Type: replace Abstract: Low-rank gradient optimization for large language models is currently divided into two categories: structured methods that rigorously identify subsp

Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agents

arXiv:2606.22528v2 Announce Type: replace Abstract: Modern LLM agents increasingly rely on context compaction, summarization, or eviction to keep long-running sessions within a token budget. We show t

Improved Predictive Performance and Interpretability for Mesomorphic Neural Networks Using Local Fidelity Regularization

arXiv:2606.29951v1 Announce Type: new Abstract: Interpretable Mesomorphic Neural Networks (IMNs) offer a promising framework that combines the predictive power of deep neural networks with the interpr

LEDGER: Scaling Agentic Document Editing with Dependency-aware Graph Retrieval

arXiv:2606.28379v1 Announce Type: cross Abstract: We introduce LEDGER to tackle the novel context engineering challenge of agentic document editing, where localized edits to long, structured documents

LLM Agents Are Latent Context Managers: Eliciting Self-Managed Context via a Proprioceptive Dashboard

model-releasesarxiv-cs-cl

arXiv:2606.30005v1 Announce Type: new Abstract: Long-horizon tool agents are bottlenecked by how their context grows toward the limits of the context window. Recent systems make context management age

LoRAShield: Data-Free Editing Alignment for Secure Personalized LoRA Sharing

arXiv:2507.07056v2 Announce Type: replace-cross Abstract: The proliferation of Low-Rank Adaptation (LoRA) models has democratized personalized text-to-image generation, enabling users to share lightwe

safetyarxiv-cs-lg

Making Multimodal LLMs Reliable Chart Data Extractors: A Benchmark and Training Framework

arXiv:2606.29808v1 Announce Type: cross Abstract: Chart data extraction, which reverse-engineers data tables from chart images, is essential for reproducibility, analysis, retrieval, and redesign. Exi

meta-pipe: An LLM-agent pipeline for end-to-end automated systematic review and meta-analysis

arXiv:2606.28363v1 Announce Type: cross Abstract: Objective: To describe the architecture and design rationale of meta-pipe, an open-source large language model (LLM)-agent pipeline that integrates th

Mitigating Batch Effects in Histopathology via Language-Mediated Robust Embedding Generation

arXiv:2606.28697v1 Announce Type: cross Abstract: Pathology foundation models (PFMs) have demonstrated strong potential across clinical and scientific applications, yet their performance is often hind

researcharxiv-cs-cl

Agents

Monte Carlo Query Search: Active Capability Assessment of AI Agents

arXiv:2512.16733v3 Announce Type: replace Abstract: Black-box AI (BBAI) systems, including foundation-model agents, are increasingly used for sequential decision making. Safe deployment requires metho

agentsarxiv-cs-ai

muFlow: Leveraging Average Images for Improving Generalisation of Deepfake Faces Detectors

arXiv:2606.30528v1 Announce Type: new Abstract: Current generative models, including GANs and diffusion models, have reached an outstanding level of photorealism, posing significant risks to privacy a

safetyarxiv-cs-cv

Multimodal Representation Alignment for Cross-modal Information Retrieval

arXiv:2506.08774v2 Announce Type: replace-cross Abstract: Different machine learning models can represent the same underlying concept in different ways. This variability is particularly valuable for i

safetyarxiv-cs-ai

MuseBench: Benchmarking Intent-Level Audiovisual Arts Understanding in MLLMs

arXiv:2606.30026v1 Announce Type: cross Abstract: Audiovisual arts encompass diverse creative disciplines, including cinema, visual arts, stage performance, and game design, where artistic meaning ari

Never Skip a Batch: Dense Learning of Temporal GNNs via Adaptive Pseudo-Supervision

arXiv:2505.12526v2 Announce Type: replace Abstract: Temporal graph networks suffer from irregular supervision in realworld dynamic graphs, as most minibatches contain few labeled events. The lack of l

OmniCoT: A Benchmark for Global and Multi-Step Panoramic Reasoning

arXiv:2606.30378v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated promising spatial reasoning capabilities, while these abilities remain underexplored in the e

Orca: The World is in Your Mind

arXiv:2606.30534v1 Announce Type: new Abstract: We introduce Orca, an initial instantiation of a general world foundation model. Orca learns a unified world latent space from multimodal world signals

researcharxiv-cs-cv

PGE-SAM: Prompt-Guided Feature Enhancement for Interactive Segmentation under Degradation

arXiv:2606.30477v1 Announce Type: new Abstract: Segment Anything Model (SAM) has revolutionized promptable image segmentation with strong zero-shot generalization. However, its performance degrades su

Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization

arXiv:2602.11351v2 Announce Type: replace Abstract: Proactive large language model (LLM) agents aim to actively plan, query, and interact over multiple turns, enabling efficient task completion beyond

RiverONE: Generating Knowledge-Intensive VLM by Simulated Quantum Machines

arXiv:2606.29966v1 Announce Type: cross Abstract: Quantum computing provides a powerful paradigm for representing and transforming high-dimensional information through superposition, entanglement, and

SABER-Math: Automated Benchmark for Information Retrieval Evaluation in Mathematics

arXiv:2606.29894v1 Announce Type: cross Abstract: As agentic AI systems tackle more complex mathematical tasks, they increasingly rely on information retrieval (IR) to search problem databases, theore

Scalable Synthesis of distributed LLM workloads through Symbolic Tensor Graphs

arXiv:2511.10480v3 Announce Type: replace-cross Abstract: Optimizing the performance of large language models (LLMs) on large-scale AI training and inference systems requires a scalable and expressive

researcharxiv-cs-ai

SciVisAgentBench: A Benchmark for Evaluating Scientific Data Analysis and Visualization Agents

arXiv:2603.29139v2 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have enabled agentic systems to translate natural-language intent into executable scientific visuali

Tutorials

See, Think, Learn: A Self-Taught Multimodal Reasoner

arXiv:2512.02456v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have achieved remarkable progress in integrating visual perception with language understanding. However, effecti

tutorialsarxiv-cs-cl

Local Ai

Smooth Scaling Laws Hide Stepwise Token Learning

arXiv:2606.29858v1 Announce Type: new Abstract: Language model loss follows remarkably regular scaling laws over model and data size, yet it remains unclear why the aggregate loss should exhibit a pow

local-aiarxiv-cs-cl

Local Ai

Spectral Perturbation of the Empirical Fisher Information Matrix under Weight Quantization

arXiv:2606.28432v1 Announce Type: cross Abstract: We study the spectral perturbation of the empirical Fisher Information Matrix (FIM) of a parametric statistical model under two structured perturbatio

local-aiarxiv-cs-ai

StarDojo: Benchmarking Open-Ended Behaviors of Agentic Multimodal LLMs in Production-Living Simulations with Stardew Valley

arXiv:2507.07445v3 Announce Type: replace Abstract: Autonomous agents navigating human society must master both production activities and social interactions, yet existing benchmarks rarely evaluate t

TUA-Bench: A Benchmark for General-Purpose Terminal-Use Agents

arXiv:2606.28480v1 Announce Type: cross Abstract: As large language models and harness frameworks continue to advance, agents operating in terminals are increasingly capable of performing a broader ra

Variance Reduction on the Camera Axis: Multi-View Score Distillation for 3D

arXiv:2606.29964v1 Announce Type: new Abstract: Score distillation turns a pretrained 2D diffusion model into a 3D generator, but the per-step gradient is estimated from a single randomly chosen view:

When Does Overlap Help? OSU-Mem and a Cell-Conditional Analysis of Trajectory Memory for LLM Agents

arXiv:2606.28376v1 Announce Type: cross Abstract: Long-horizon large language model (LLM) agents accumulate interaction trajectories that quickly exceed any practical prompt budget, and existing memor

When Prices Double in a Week: Forecasting of Agricultural Volatility in Import-Isolated Markets

arXiv:2606.29248v1 Announce Type: new Abstract: Vegetable prices in Sri Lanka are highly volatile because the market is largely import-isolated, so supply disruptions quickly drive prices up. This stu

researcharxiv-cs-lg

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection

arXiv:2606.30587v1 Announce Type: cross Abstract: Researchers and practitioners increasingly apply Large Language Models (LLMs) for automated vulnerability detection. Recent work has shown that LLMs a

safetyarxiv-cs-ai

XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generation

arXiv:2412.15529v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) synergizes the retrieval of pertinent data with the generative capabilities of Large Language Models (LLM

A Multi-Attribute Latent Space for Visual Analysis of Watches

arXiv:2606.27897v1 Announce Type: new Abstract: We present a design rationale, embedding model, and interactive visual-analysis system for exploring large wristwatch collections through heterogeneous

A Tree-of-Thoughts Inspired Hybrid Approach for Legal Case Judgement Summarization using LLMs

model-releasesarxiv-cs-cl

arXiv:2606.28044v1 Announce Type: new Abstract: In recent times, Large Language Models (LLMs) are increasingly being used for legal case judgement summarization. Most prior works have tried traditiona

Building a Scalable, Reproducible, Evaluatable, and Closed-Loop Simulation Environment Foundation for Embodied Intelligence Cloud-Native Simulation Infrastructure for Embodied Intelligence Training, Evaluation, and Data Collection

model-releasesarxiv-cs-ro

arXiv:2606.27962v1 Announce Type: new Abstract: This paper presents a cloud-native simulation infrastructure framework for embodied intelligence that supports large-scale training, standardized evalua

Can Generative Artificial Intelligence Survive Data Contamination? Theoretical Guarantees under Contaminated Recursive Training

arXiv:2602.16065v2 Announce Type: replace-cross Abstract: As artificial intelligence (AI)-generated content proliferates, models are increasingly trained on their own outputs, risking progressive degr

safetyarxiv-cs-ai

Tutorials

CBD: API-Only LLM Black-Box Unlearning through Controlled Behavioral Divergence

arXiv:2606.27683v1 Announce Type: cross Abstract: Edge devices increasingly invoke large language models (LLMs) through API services for context aware edge intelligence, while edge generated data may

tutorialsarxiv-cs-ai

DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domain

arXiv:2504.16116v4 Announce Type: replace-cross Abstract: The Web3 ecosystem, underpinned by cryptographic primitives and decentralized consensus, represents a high-stakes environment where software v

FoggyTrust: Robust Federated Learning with Hierarchical Trust Networks

arXiv:2606.27622v1 Announce Type: new Abstract: Byzantine-robust federated learning seeks to protect distributed model training from malicious or corrupted clients without requiring access to their pr