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@jerryjliu0 — Founder & CEO of @llama_index — on Venture with Grace, sharing why data is at the center of the agentic AI boom. AI agents are…

@jerryjliu0 — Founder & CEO of @llama_index — on Venture with Grace, sharing why data is at the center of the agentic AI boom. AI agents are proliferating rapidly — and with them comes an explosion of

agentsjerry-liu--x

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KG-FairDiff: Knowledge Graph-Guided Prompt Refinement for Demographically Fair Text-to-Image Generation

DGX agent

arXiv:2606.01282v1 Announce Type: new Abstract: Text-to-Image (TTI) systems are now everyday infrastructure for journalism, education, advertising, and public communication, and the demographic and cu

safetyarxiv-cs-cv

2 Jun 2026

KnowledgeBerg: Evaluating Systematic Knowledge Coverage and Compositional Reasoning in Large Language Models

arXiv:2604.17621v2 Announce Type: replace Abstract: Many real-world questions appear deceptively simple yet implicitly demand two capabilities: (i) systematic coverage of a bounded knowledge universe

Leaf Spectral Reflectance Prediction Using Multi-Head Attention Neural Networks

arXiv:2606.01432v1 Announce Type: new Abstract: Accurate modeling of leaf spectral reflectance from physiological and biochemical traits is essential for advancing remote sensing applications in plant

researcharxiv-cs-lg

Tutorials

LLMs Need Encoders for Semantic IDs Too

arXiv:2606.00324v1 Announce Type: cross Abstract: Multimodal LLMs use dedicated encoders to bridge non-language modalities (vision encoders for images, depth models for audio codec tokens) because raw

tutorialsarxiv-cs-ai

LocalSearchBench: Benchmarking Agentic Search in Real-World Local Life Services

arXiv:2512.07436v3 Announce Type: replace Abstract: Recent advances in large reasoning models LRMs have enabled agentic search systems to perform complex multi-step reasoning across multiple sources.

Applications

LongAttnComp: Cross-Family Context Compression for Long-Context Reasoning

arXiv:2606.01336v1 Announce Type: new Abstract: As real-world applications increasingly require processing inputs of 100k+ tokens, the gap between context length and inference efficiency has become a

applicationsarxiv-cs-cl

Med-HEAL: Analyzing and Mitigating Hallucinations in Medical LLMs with Hallucination-Aware In-Context Learning

arXiv:2606.01301v1 Announce Type: new Abstract: Hallucinations in medical large language models (LLMs) pose serious risks for clinical decision support, particularly when models must reason over compl

MemPro: Agentic Memory Systems as Evolvable Programs

arXiv:2606.00619v1 Announce Type: cross Abstract: Long-horizon autonomous agents require memory systems to retain historical information, track evolving states, and reuse relevant knowledge beyond fin

Local Ai

MENTIS: What Belief Changes Under Alignment? Measuring Multi-Scale Latent Torsion in Language Models

arXiv:2606.01060v1 Announce Type: cross Abstract: Preference alignment has substantially improved the observable behavior of large language models, yet it remains unclear what alignment changes intern

local-aiarxiv-cs-ai

Model-Based Quality Assessment for Massively Multilingual Parallel Data

arXiv:2606.00285v1 Announce Type: new Abstract: Large-scale multilingual bitext often contains two distinct problems: non-parallel sentence pairs and low-quality translations. We decompose model-based

PHASOR: Phase-Anchored Universal Action Representations for Humanoid Embodiments

arXiv:2606.01851v1 Announce Type: new Abstract: Learning a good action embedding space is fundamental to scalable robot policy learning, yet existing methods treat action latents as task-specific inte

safetyarxiv-cs-ro

Plausibility Is Not Prediction: Contrastive Evidence for LLM-Based Cellular Perturbation Reasoning

arXiv:2606.01042v1 Announce Type: cross Abstract: Perturbation experiments are central to understanding cellular mechanisms, but remain costly and sparse, motivating prediction of gene expression resp

researcharxiv-cs-ai

Applications

Predicting the risk of colorectal anastomotic leak based on preoperative mapping of the blood supply of the bowel

arXiv:2606.02156v1 Announce Type: cross Abstract: Anastomotic leak remains one of the most serious complications following colorectal cancer surgery, substantially affecting patient outcomes, recovery

applicationsarxiv-cs-ai

Local Ai

PropLLM: Propagation-Aware Scene Reconstruction for Network Fault Diagnosis

arXiv:2606.00582v1 Announce Type: new Abstract: Network faults propagate layer by layer along topology and protocol dependencies, yet operations systems typically observe only symptomatic alerts at th

local-aiarxiv-cs-ai

RadioMaster: Multi-Agent System for Autonomous Radio Signal Generation

arXiv:2606.01862v1 Announce Type: cross Abstract: Translating user intents into physical radio signals represents the critical yet notoriously tedious final step in wireless prototyping, as it require

REAL: Resolving Knowledge Conflicts in Knowledge-Intensive Visual Question Answering via Reasoning-Pivot Alignment

arXiv:2602.14065v2 Announce Type: replace Abstract: Knowledge-intensive Visual Question Answering (KI-VQA) frequently suffers from severe knowledge conflicts caused by the inherent limitations of open

Reconstructing Content via Collaborative Attention to Improve Multimodal Embedding Quality

arXiv:2603.01471v2 Announce Type: replace-cross Abstract: Multimodal embedding models, rooted in multimodal large language models (MLLMs), have yielded significant performance improvements across dive

researcharxiv-cs-lg

RescueBench: Can Embodied Agents Save Lives in the Wild ?

model-releasesarxiv-cs-cv

arXiv:2606.01848v1 Announce Type: new Abstract: Search-and-rescue (SAR) requires embodied agents to explore unfamiliar environments under multimodal uncertainty, perform multi-stage interactions, and

Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence

arXiv:2606.00570v1 Announce Type: cross Abstract: Parameter-based knowledge editing updates the internal knowledge of large language models (LLMs) via localized weight modifications and has attracted

RoboDream: Compositional World Models for Scalable Robot Data Synthesis

arXiv:2606.02577v1 Announce Type: cross Abstract: Scaling robot learning requires large-scale, diverse demonstrations, yet real-world data collection via teleoperation remains prohibitively expensive

safetyarxiv-cs-cv

Sandboxed Coding Agents are Competitive Omni-modal Task Solvers

arXiv:2606.00579v1 Announce Type: new Abstract: As multimodal LLMs increasingly target video and audio, it is often assumed that such tasks require native omnimodal models. We show that this is not al

Scaling Pre-training to One Hundred Billion Data for Vision Language Models

arXiv:2502.07617v2 Announce Type: replace Abstract: We provide an empirical investigation of the potential of pre-training vision-language models on an unprecedented scale: 100 billion examples. We fi

researcharxiv-cs-cv

SceneSmith: Agentic Generation of Simulation-Ready Indoor Scenes

arXiv:2602.09153v2 Announce Type: replace-cross Abstract: Simulation has become a key tool for training and evaluating home robots at scale, yet existing environments fail to capture the diversity and

Self-Revising Discovery Systems for Science: A Categorical Framework for Agentic Artificial Intelligence

arXiv:2606.01444v1 Announce Type: new Abstract: Scientific discovery is not only answer generation but revision of the representational regime in which evidence, artifacts, operations, and verifiers a

SHERLOCK: Towards Dynamic Knowledge Adaptation in LLM-enhanced E-commerce Risk Management

arXiv:2510.08948v4 Announce Type: replace-cross Abstract: Effective e-commerce risk management requires in-depth case investigations to identify emerging fraud patterns in highly adversarial environme

Simulating Macroeconomic Expectations in Survey Experiments with LLM-based Economic Agents

arXiv:2505.17648v5 Announce Type: replace-cross Abstract: We introduce a framework for simulating macroeconomic expectations in survey experiments using LLM-based economic agents (LLM Agents). We cons

researcharxiv-cs-ai

SIRI: Self-Internalizing Reinforcement Learning with Intrinsic Skills for LLM Agent Training

arXiv:2606.02355v1 Announce Type: new Abstract: Long-horizon LLM agents can benefit from reusable skills, yet existing skill-based methods often rely on external skill generators during training or pe

SkillRevise: Improving LLM-Authored Agent Skills via Trace-Conditioned Skill Revision

arXiv:2606.01139v1 Announce Type: new Abstract: Agent skills are procedural artifacts that enable LLM agents to execute workflows, verify constraints, and recover from failures. Existing self-evolving

SkillSmith: Co-Evolving Skills and Tools for Self-Improving Agent Systems

arXiv:2606.01314v1 Announce Type: new Abstract: Recent self-evolving agents have shown that skills can be discovered, refined, and accumulated through execution. However, existing skill-evolution fram

Soft-NBCE: Entropy-Weighted Chunk Fusion for Long-Context

arXiv:2606.01101v1 Announce Type: cross Abstract: The quadratic complexity of self-attention remains a bottleneck for Large Language Models (LLMs) processing ultra-long contexts. The Naive Bayes Cogni

researcharxiv-cs-ai

SortingHat: Redefining Operating Systems Education with a Tailored Digital Teaching Assistant

arXiv:2606.00015v1 Announce Type: cross Abstract: Operating Systems (OS) courses are among the most challenging in computer science education due to the complexity of internal structures and the diver

Spatial-Temporal Decoupled Reference Conditioning for Identity-Preserving Text-to-Video Generation

arXiv:2606.02441v1 Announce Type: new Abstract: Identity-preserving video generation (IPVG) aims to synthesize high-fidelity videos that follow text prompts while faithfully preserving a reference ide

safetyarxiv-cs-cv

// State-Externalizing Harnesses // A new paradigm is emerging on how to effectively build agents and harnesses. If there is a state that th…

// State-Externalizing Harnesses // A new paradigm is emerging on how to effectively build agents and harnesses. If there is a state that the environment can maintain reliably, it probably doesn't bel

safetydair-ai--x

SuperMemory-VQA: An Egocentric Visual Question-Answering Benchmark for Long-Horizon Memory

model-releasesarxiv-cs-cv

arXiv:2606.00825v1 Announce Type: new Abstract: AI glasses present a compelling platform for AI agents to serve as personalized memory assistants. To be genuinely useful, such systems must move beyond

T-CLIP: Enabling Thermal Perception for Contrastive Language-Image Pretraining

arXiv:2606.00673v1 Announce Type: new Abstract: Thermal imaging offers a powerful alternative to visible-spectrum vision under challenging conditions such as low illumination and adverse weather, yet

researcharxiv-cs-cv

UniD^3: A Knowledge Graph-Enhanced RAG Framework for Drug-Disease Discovery and Reasoning

arXiv:2606.01394v1 Announce Type: new Abstract: Systematic characterization of drug-disease relationships is essential for drug discovery and repurposing, yet is hindered by the heterogeneity and rapi

Unified Context Evolution for LLM Agents

arXiv:2606.02304v1 Announce Type: new Abstract: LLM-based agents can solve multi-step interactive tasks by combining reasoning with environment feedback, yet each episode starts from the same fixed co

agentsarxiv-cs-cl

VideoBrain: Learning Adaptive Frame Sampling for Long Video Understanding

arXiv:2602.04094v2 Announce Type: replace Abstract: Long-form video understanding remains challenging for Vision-Language Models (VLMs) due to the inherent tension between computational constraints an

agentsarxiv-cs-cv

VocSim: A Training-free Benchmark for Zero-shot Content Identity in Single-source Audio

arXiv:2512.10120v2 Announce Type: replace-cross Abstract: General-purpose audio representations aim to map acoustically variable instances of the same event to nearby points, resolving content identit

Annotations Are Not All You Need: A Cross-modal Knowledge Transfer Network for Unsupervised Temporal Sentence Grounding

arXiv:2605.30742v1 Announce Type: new Abstract: This paper addresses the task of temporal sentence grounding (TSG). Although many respectable works have made decent achievements in this important topi

safetyarxiv-cs-cv

Beyond Static Dialogues: Benchmarking Realistic, Heterogeneous, and Evolving Long-Term Memory

arXiv:2605.31086v1 Announce Type: new Abstract: In existing memory benchmarks for Large Language Models (LLMs), the evaluated dialogue sessions often lack long-term semantic consistency, and the under

Tutorials

Constrained Flow Optimization via Sequential Fine Tuning for Molecular Design

arXiv:2605.30610v1 Announce Type: new Abstract: Adapting generative foundation models, in particular diffusion and flow models, to optimize given reward functions (e.g., binding affinity) while satisf

tutorialsarxiv-cs-lg

Counterfactual Evaluation Reveals Hidden Capability Profiles in Clinical LLMs and Agents

arXiv:2605.30590v1 Announce Type: cross Abstract: Two clinical AI systems can score nearly identically on coverage-based rubrics yet behave radically differently when their patient inputs change: one

Demo3：Browser Agent

Demo3 showcases Qwen's browser agent capabilities, likely demonstrating an AI system's ability to autonomously interact with web browsers to perform tasks such as navigation, form filling, or informat

agentsqwen--x

EvoGens: A Population-Based Heuristic Search Framework for Scientific Idea Generation

arXiv:2605.30961v1 Announce Type: new Abstract: Generating novel research ideas is fundamental to scientific progress. While Large Language Models (LLMs) show promise in assisting this process, existi

researcharxiv-cs-cl

FOCUS: Forcing In-Context Object Localization through Visual Support Constraints and Policy Optimization

arXiv:2605.31145v1 Announce Type: cross Abstract: In-context localization (ICL) seeks to localize a target object specified by a small set of support examples in a query image, operating on the fly wi

ForecastCompass: Guiding Agentic Forecasting with Adaptive Factor Memory

model-releasesarxiv-cs-lg

arXiv:2605.30858v1 Announce Type: new Abstract: Agentic forecasting is important for decision-making in dynamic environments, but it remains challenging because agents must reason from incomplete, tim