Search: “llm”

Towards Atoms of Large Language Models

arXiv:2509.20784v3 Announce Type: replace-cross Abstract: The fundamental representational units (FRUs) of large language models (LLMs) remain undefined, limiting further understanding of their underl

Applications

Towards Effective Long-Video Event Prediction via Multi-Level Event Semantics Mining

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2605.31069v1 Announce Type: cross Abstract: Accurately predicting future events is fundamental to content understanding and decision-making across various domains. While prior research has prima

applicationsarxiv-cs-cl

1 Jun 2026

TRACE: Discovering Task-Specific Parameter via Adaptation-Aware Probing for Continual Fine-Tuning

arXiv:2605.31025v1 Announce Type: new Abstract: In real-world deployment, LLMs are often adapted continually across tasks to keep LLMs up-to-date in production, where new fine-tuning should preserve p

TUX: Measuring Human--AI Tacit Understanding

arXiv:2605.30930v1 Announce Type: cross Abstract: As large language models (LLMs) increasingly act as collaborative partners, human--AI alignment is often evaluated through explicit task success, accu

Unifying and Optimizing Data Values for Selection via Sequential Decision-Making

arXiv:2502.04554v2 Announce Type: replace Abstract: Data selection has emerged as a crucial downstream application of data valuation, yet the theoretical foundations for using data values in selection

What Gets Unmasked First? Trajectory Analysis of Diffusion Models for Graph-to-Text Generation

arXiv:2605.31564v1 Announce Type: cross Abstract: We present the first systematic study of masked diffusion language models (MDLMs) for graph-to-text generation. We analyze MDLM generation trajectorie

Local Ai

When English Rewrites Local Knowledge: Global Narrative Dominance in Large Language Models

arXiv:2605.30481v1 Announce Type: new Abstract: Large language models (LLMs) are widely used as cross-lingual knowledge interfaces. However, culturally grounded questions often reflect globally domina

local-aiarxiv-cs-cl

A Modular Architecture for Typologically Controlled Lexicon Generation

arXiv:2605.28824v1 Announce Type: new Abstract: Constructing artificial lexicons that are pronounceable, typologically plausible, and semantically structured remains an open challenge in computational

safetyarxiv-cs-cl

Agent4Edu: Generating Learner Response Data by Generative Agents for Intelligent Education Systems

arXiv:2501.10332v2 Announce Type: replace-cross Abstract: Personalized learning represents a promising educational strategy within intelligent educational systems, aiming to enhance learners' practice

AgentCVR: Active Multi-Agent Cross-Video Reasoning via Script-Simulated Reinforcement Learning

model-releasesarxiv-cs-cv

arXiv:2605.29643v1 Announce Type: new Abstract: Cross-Video Reasoning (CVR) has emerged as a critical frontier in multimodal intelligence, requiring models to retrieve, align, and aggregate evidence d

Local Ai

AsymVLM: Asymmetric Token Pruning for Efficient Vision-Language Model Inference

arXiv:2605.29535v1 Announce Type: new Abstract: Vision-Language Models (VLMs) process thousands of visual tokens per image alongside comparatively few text tokens, yet existing compression methods tre

local-aiarxiv-cs-lg

Automating Low-Risk Code Review at Meta: RADAR, Risk Calibration, and Review Efficiency

arXiv:2605.30208v1 Announce Type: cross Abstract: AI-assisted coding tools have altered software production. At Meta, significant lines of code per human-landed diff grew by 105.9% year over year and

BEAMS: Benchmarking and Evaluating AI for Modeling and Simulation

arXiv:2605.28994v1 Announce Type: new Abstract: AI tools to support real world decision making must be able to build simulation models that inform their recommendations and render them interpretable.

Beyond 3D VQAs: Injecting 3D Spatial Priors into Vision-Language Models for Enhanced Geometric Reasoning

arXiv:2605.30231v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) often struggle with robust 3D spatial reasoning. Prevailing methods that rely on fine-tuning with 3D visual question-ans

Beyond Recall: Behavioral Specification as an Interpretive Layer for AI Personalization

arXiv:2605.28969v1 Announce Type: cross Abstract: If an AI agent makes decisions on a person's behalf, those decisions must align with its user. We introduce representational accuracy to measure how f

Code-QA-Bench: Separating Code Reasoning from Documentation Memorization in Repository-Level QA

arXiv:2605.29277v1 Announce Type: cross Abstract: We present Code-QA-Bench, a fully automated framework for synthesizing repository-level code understanding benchmarks that separates genuine code comp

CodeEvolve: an open source evolutionary coding agent for algorithmic discovery and optimization

arXiv:2510.14150v5 Announce Type: replace Abstract: We introduce CodeEvolve, an open-source framework that couples large language models with island-based evolutionary search for end-to-end algorithmi

COMPOSE: Composing Future Theorems from Citations and Formal Structure

arXiv:2605.30333v1 Announce Type: new Abstract: A plausible future mathematical claim must satisfy two constraints: it should follow the direction of prior work and respect the formal dependencies tha

Controlling the Risk of Corrupted Contexts for Language Models via Early-Exiting

arXiv:2510.02480v3 Announce Type: replace Abstract: Large language models (LLMs) can be influenced by harmful or irrelevant context, which can significantly harm model performance on downstream tasks.

CorPipe at CRAC 2026: Empty Nodes and Cross-Lingual Transfer in Multilingual Coreference Resolution

arXiv:2605.30133v1 Announce Type: new Abstract: We introduce CorPipe 26, our winning submission to the CRAC 2026 Shared Task on Multilingual Coreference Resolution. The fifth edition of this shared ta

researcharxiv-cs-cl

CRITIC-R1: Learning Structured Critics for Retrieval-Augmented Generation

arXiv:2605.29886v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves knowledge-intensive question answering by incorporating external evidence. However, existing RAG methods

Croissant Tasks: A Metadata Format for Reproducible Machine Learning Evaluations

arXiv:2605.29786v1 Announce Type: new Abstract: Reproducibility is fundamental to the scientific method, yet remains a critical challenge in machine learning. Contributing factors include underspecifi

Hardware

DFlash: Block Diffusion for Flash Speculative Decoding

arXiv:2602.06036v2 Announce Type: replace Abstract: Autoregressive large language models (LLMs) deliver strong performance but require inherently sequential decoding, leading to high inference latency

hardwarearxiv-cs-cl

Do not be greedy, Think Twice: Sampling and Selection for Document-level Information Extraction

arXiv:2601.18395v2 Announce Type: replace Abstract: Document-level Information Extraction (DocIE) aims to produce an output template with the entities, relations, and events of interest occurring in t

researcharxiv-cs-cl

E-valuator: Reliable Agent Verifiers with Sequential Hypothesis Testing

arXiv:2512.03109v2 Announce Type: replace-cross Abstract: Agentic AI systems execute a sequence of actions, such as reasoning steps or tool calls, in response to a user prompt. To evaluate the success

EAPO: Enhancing Policy Optimization with On-Demand Expert Assistance

arXiv:2509.23730v2 Announce Type: replace Abstract: Large language models (LLMs) have recently advanced in reasoning when optimized with reinforcement learning (RL) under verifiable rewards. Existing

Efficient Training-Free Multi-Token Prediction via Embedding-Space Probing

arXiv:2603.17942v2 Announce Type: replace Abstract: Large Language Models (LLMs) possess latent multi-token prediction (MTP) abilities despite being trained only for next-token generation. We introduc

researcharxiv-cs-cl

EvoRubric: Self-Evolving Rubric-Driven RL for Open-Ended Generation

arXiv:2605.29847v1 Announce Type: new Abstract: Reinforcement Learning (RL) has significantly advanced Large Language Models (LLMs) in verifiable domains, but aligning models for open-ended generation

safetyarxiv-cs-cl

Tutorials

Feedback-to-Rubrics: Can We Learn Expert Criteria from Inline Comments?

arXiv:2605.29857v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for writing and review support, but their usefulness depends on context-dependent criteria, such as e

tutorialsarxiv-cs-lg

Fingerprinting Inference Systems of Large Language Models

arXiv:2605.29979v1 Announce Type: cross Abstract: The behavior of LLMs does not depend solely on the model itself. Components of the inference system, such as the inference engine, attention backend,

researcharxiv-cs-lg

Formalizing Mathematics at Scale

arXiv:2605.29955v1 Announce Type: new Abstract: We present AutoformBot, a multi-agent system for building an Autoformalized Textbook Library At Scale (Atlas) in Lean 4. AutoformBot orchestrates thousa

From Context Shift to Stylistic Collapse: Why Training Objectives Matter More Than Scale

arXiv:2605.28826v1 Announce Type: new Abstract: In modern LLMs, linguistic features function not as stylistic artifacts but as probes of probability mass, allocated under training alignment objectives

safetyarxiv-cs-cl

Applications

Generative Spatiotemporal Intent Sequence Recommendation via Implicit Reasoning in Amap

arXiv:2605.28888v1 Announce Type: cross Abstract: Real-world user behavior rarely consists of isolated actions; instead, it often forms intent flows governed by spatiotemporal dependencies. To provide

applicationsarxiv-cs-lg

GenesisFunc: Multi-Agent Data Generation for Accurate and Generalizable Function-Calling

arXiv:2605.28835v1 Announce Type: cross Abstract: Large Language Models (LLMs) extend their capabilities through function-calling (FC), which relies on training data with high quality, diversity, and

Good SFT Optimizes for SFT, Better SFT Prepares for Reinforcement Learning

arXiv:2602.01058v2 Announce Type: replace-cross Abstract: Post-training of reasoning LLMs is a holistic process that typically consists of an offline SFT stage followed by an online reinforcement lear

GPF-LiveNews: A Streaming Evaluation Protocol for Group-Conditioned Framing in Large Language Models

arXiv:2605.28848v1 Announce Type: cross Abstract: Deployed language models are evaluated in a non-stationary environment: model versions, retrieval layers, safety systems, and real-world inputs all ch

Grammar-Aware Literate Generative Mathematical Programming with Compiler-in-the-Loop

arXiv:2601.17670v2 Announce Type: replace-cross Abstract: Mathematical programming is widely employed across various sectors - such as logistics, energy, and workforce planning - to model and solve in

GrowLoop: Self-Evolving Conversation Evaluation Seeded by Human

arXiv:2605.28882v1 Announce Type: cross Abstract: With the rapid advancement of large language models, evaluating human-likeness in open-ended conversation has become increasingly important. However,

Hallucination Detection-Guided Preference Optimization for Clinical Summarization

arXiv:2605.28910v1 Announce Type: cross Abstract: Large language models (LLMs) have shown promise on summarization tasks, but they often produce hallucinations, which are unsupported or incorrect stat

Improving Collaborative Storytelling with a Multi-Agent Framework Based on Large Language Models

arXiv:2605.29625v1 Announce Type: new Abstract: The topic of Co-creation, i.e., AI agents interacting with humans to generate outputs (e.g., art), has gained significant attention recently. However, m

Inferring the Size of Large Language Models From Popular Text Memorization

model-releasesarxiv-cs-lg

arXiv:2605.29223v1 Announce Type: new Abstract: The parameter counts of the most widely used large language models (LLMs) are often withheld by their developers, leaving model size -- a primary refere

KairosAgent: Agentic Time Series Forecasting with Fused Semantic Reasoning

arXiv:2605.30002v1 Announce Type: new Abstract: Cross-domain multimodal time series forecasting is a challenging task, requiring models to integrate precise numerical comprehension, cross-domain seman

KBF: Knowledge Boundary as Fingerprint for Language Model and Black-Box API Auditing

arXiv:2605.29524v1 Announce Type: cross Abstract: Relay and reseller APIs increasingly intermediate access to large language models (LLMs), but users have no direct way to verify that a claimed endpoi

Label-Free Reinforcement Learning via Cross-Model Entropy

arXiv:2605.29009v1 Announce Type: cross Abstract: Post-training large language models with reinforcement learning is bottlenecked by the reward signal. Existing approaches require either ground-truth

Large language models reorganize representational geometry during in-context learning

arXiv:2605.28854v1 Announce Type: new Abstract: Large language models (LLMs) exhibit remarkable flexibility: they can adapt to novel tasks from in-context examples without any parameter updates, a cap

Learning Design Skills as Memory Policies for Agentic Photonic Inverse Design

arXiv:2605.29421v1 Announce Type: new Abstract: Photonic crystal fiber (PCF) inverse design remains challenging because candidate geometries must satisfy coupled optical targets under expensive electr

Learning to Choose: An Empowerment-Guided Multi-Agent System with semantic communication for Adaptive Method Selection

arXiv:2605.30042v1 Announce Type: new Abstract: Automating scientific computing workflows requires more than generating executable code: autonomous systems must also select appropriate computational s

LiveSVG: Zero-Shot SVG Animation via Video Generation

model-releasesarxiv-cs-cv

arXiv:2605.30174v1 Announce Type: new Abstract: We introduce LiveSVG, a zero-shot approach for generating Scalable Vector Graphics (SVG) animations using video diffusion models. Current SVG animation