Search: “llm”

PlankFormer: Robust Plankton Instance Segmentation via MAE-Pretrained Vision Transformers and Pseudo Community Image Generation

arXiv:2604.17856v1 Announce Type: new Abstract: Plankton monitoring is essential for assessing aquatic ecosystems but is limited by the labor-intensive nature of manual microscopic analysis. Automatin

applicationsarxiv-cs-cv

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Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning

DGX agent

arXiv:2502.02871v2 Announce Type: replace Abstract: Scientific reasoning, the process through which humans apply logic, evidence, and critical thinking to explore and interpret scientific phenomena, i

researcharxiv-cs-cl

21 Apr 2026

PrefixMemory-Tuning: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention

arXiv:2506.13674v3 Announce Type: replace Abstract: Parameter-Efficient Fine-Tuning (PEFT) methods have become crucial for rapidly adapting large language models (LLMs) to downstream tasks. Prefix-Tun

Program Structure-aware Language Models: Targeted Software Testing beyond Textual Semantics

model-releasesarxiv-cs-lg

arXiv:2604.17715v1 Announce Type: cross Abstract: Recent advances in large language models for test case generation have improved branch coverage via prompt-engineered mutations. However, they still l

Real-World Intelligence ChatGPT Images 2.0 has an updated knowledge cutoff of December 2025 and intelligence that allows it to expertly hand…

Real-World Intelligence ChatGPT Images 2.0 has an updated knowledge cutoff of December 2025 and intelligence that allows it to expertly handle tasks end-to-end, from copywriting to analysis to design

applicationsopenai--x

ReCap: Lightweight Referential Grounding for Coherent Story Visualization

model-releasesarxiv-cs-cv

arXiv:2604.18575v1 Announce Type: new Abstract: Story Visualization aims to generate a sequence of images that faithfully depicts a textual narrative that preserve character identity, spatial configur

REFLEX: Reference-Free Evaluation of Log Summarization via Large Language Model Judgment

arXiv:2511.07458v2 Announce Type: replace Abstract: Evaluating log summarization systems is challenging due to the lack of high-quality reference summaries and the limitations of existing metrics like

applicationsarxiv-cs-cl

Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Framework

arXiv:2604.18145v1 Announce Type: new Abstract: Automated medical report generation for 3D PET/CT imaging is fundamentally challenged by the high-dimensional nature of volumetric data and a critical s

local-aiarxiv-cs-cv

Rethinking Meeting Effectiveness: A Benchmark and Framework for Temporal Fine-grained Automatic Meeting Effectiveness Evaluation

arXiv:2604.17260v1 Announce Type: new Abstract: Evaluating meeting effectiveness is crucial for improving organizational productivity. Current approaches rely on post-hoc surveys that yield a single c

Rethinking the Comparison Unit in Sequence-Level Reinforcement Learning: An Equal-Length Paired Training Framework from Loss Correction to Sample Construction

arXiv:2604.17328v1 Announce Type: new Abstract: This paper investigates the length problem in sequence-level relative reinforcement learning. We observe that, although existing methods partially allev

Retrieval-Augmented Multimodal Model for Fake News Detection

arXiv:2604.18112v1 Announce Type: new Abstract: In recent years, multimodal multidomain fake news detection has garnered increasing attention. Nevertheless, this direction presents two significant cha

Revisiting Entropy in Reinforcement Learning for Large Reasoning Models

arXiv:2511.05993v3 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a prominent paradigm for enhancing the reasoning capabilities of large language

local-aiarxiv-cs-cl

RISC-V Functional Safety for Autonomous Automotive Systems: An Analytical Framework and Research Roadmap for ML-Assisted Certification

arXiv:2604.17391v1 Announce Type: cross Abstract: RISC-V is emerging as a viable platform for automotive-grade embedded computing, with recent ISO 26262 ASIL-D certifications demonstrating readiness f

RoMathExam: A Longitudinal Dataset of Romanian Math Exams (1895-2025) with a Seven-Decade Core (1957-2025)

arXiv:2604.16392v1 Announce Type: cross Abstract: AI in Education research increasingly relies on authentic, curriculum-grounded assessment data, yet large, well-structured exam corpora remain scarce

RoTRAG: Rule of Thumb Reasoning for Conversation Harm Detection with Retrieval-Augmented Generation

arXiv:2604.17301v1 Announce Type: new Abstract: Detecting harmful content in multi turn dialogue requires reasoning over the full conversational context rather than isolated utterances. However, most

Same Claim, Different Judgment: Benchmarking Scenario-Induced Bias in Multilingual Financial Misinformation Detection

arXiv:2601.05403v2 Announce Type: replace Abstract: Large language models (LLMs) have been widely applied across various domains of finance. Since their training data are largely derived from human-au

Hardware

Scalable and Adaptive Parallel Training of Graph Transformer on Large Graphs

arXiv:2604.16715v1 Announce Type: cross Abstract: Graph foundation models have demonstrated remarkable adaptability across diverse downstream tasks through large-scale pretraining on graphs. However,

hardwarearxiv-cs-lg

ScienceBoard: Evaluating Multimodal Autonomous Agents in Realistic Scientific Workflows

arXiv:2505.19897v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have extended their impact beyond Natural Language Processing, substantially fostering the development of interdi

Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Reasoning

arXiv:2505.13353v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed for understanding large codebases, but whether they understand operational semantics of long

Agents

Sensorimotor Self-Recognition in Multimodal Large Language Model-Driven Robots

arXiv:2505.19237v2 Announce Type: replace-cross Abstract: Self-recognition -- the ability to maintain an internal representation of one's own body within the environment -- underpins intelligent, auto

agentsarxiv-cs-ro

SIGMA: A Semantic-Grounded Instruction-Driven Generative Multi-Task Recommender at AliExpress

arXiv:2602.22913v2 Announce Type: replace-cross Abstract: With the rapid evolution of Large Language Models (LLMs), generative recommendation is gradually reshaping the paradigm of recommender systems

applicationsarxiv-cs-lg

Sparse Feature Coactivation Reveals Causal Semantic Modules in Large Language Models

arXiv:2506.18141v3 Announce Type: replace Abstract: We identify semantically coherent, context-consistent network components in large language models (LLMs) using coactivation of sparse autoencoder (S

SpeechMedAssist: Efficiently and Effectively Adapting Speech Language Models for Medical Consultation

arXiv:2601.04638v2 Announce Type: replace Abstract: Medical consultations are intrinsically speech-centric. However, most prior works focus on long-text-based interactions, which are cumbersome and pa

SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation

arXiv:2512.21204v2 Announce Type: replace Abstract: Human infants, with only a few hundred hours of speech exposure, acquire basic units of new languages, highlighting a striking efficiency gap compar

ST-pi: Structured SpatioTemporal VLA for Robotic Manipulation

arXiv:2604.17880v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved great success on general robotic tasks, but still face challenges in fine-grained spatiotemporal man

local-aiarxiv-cs-cv

Stable Language Guidance for Vision-Language-Action Models

arXiv:2601.04052v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have demonstrated impressive capabilities in generalized robotic control; however, they remain notoriously

Still Between Us? Evaluating and Improving Voice Assistant Robustness to Third-Party Interruptions

arXiv:2604.17358v1 Announce Type: new Abstract: While recent Spoken Language Models (SLMs) have been actively deployed in real-world scenarios, they lack the capability to discern Third-Party Interrup

applicationsarxiv-cs-cl

Structure-Aware Diversity Pursuit as an AI Safety Strategy against Homogenization

arXiv:2601.06116v2 Announce Type: replace-cross Abstract: Generative AI models reproduce the biases in the training data and can further amplify them through mode collapse. We refer to the resulting h

SVL: Goal-Conditioned Reinforcement Learning as Survival Learning

arXiv:2604.17551v1 Announce Type: new Abstract: Standard approaches to goal-conditioned reinforcement learning (GCRL) that rely on temporal-difference learning can be unstable and sample-inefficient d

researcharxiv-cs-lg

Synthia: Scalable Grounded Persona Generation from Social Media Data

arXiv:2507.14922v2 Announce Type: replace Abstract: Persona-driven simulations are increasingly used in computational social science, yet their validity critically depends on the fidelity of the under

T-REN: Learning Text-Aligned Region Tokens Improves Dense Vision-Language Alignment and Scalability

arXiv:2604.18573v1 Announce Type: new Abstract: Despite recent progress, vision-language encoders struggle with two core limitations: (1) weak alignment between language and dense vision features, whi

local-aiarxiv-cs-cv

Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation

arXiv:2510.09671v2 Announce Type: replace Abstract: Table Question Answering (TQA) aims to answer natural language questions about tabular data, often accompanied by additional contexts such as text p

The Geometric Canary: Predicting Steerability and Detecting Drift via Representational Stability

arXiv:2604.17698v1 Announce Type: cross Abstract: Reliable deployment of language models requires two capabilities that appear distinct but share a common geometric foundation: predicting whether a mo

The Provenance Gap in Clinical AI: Evidence-Traceable Temporal Knowledge Graphs for Rare Disease Reasoning

arXiv:2604.17114v1 Announce Type: new Abstract: Frontier large language models generate clinically accurate outputs, but their citations are often fabricated. We term this the Provenance Gap. We teste

Tool Learning Needs Nothing More Than a Free 8B Language Model

arXiv:2604.17739v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a prevalent paradigm for training tool calling agents, which typically requires online interactive environments

ToxiFrench: Benchmarking and Enhancing Language Models via CoT Fine-Tuning for French Toxicity Detection

arXiv:2508.11281v3 Announce Type: replace Abstract: Detecting toxic content using language models is crucial yet challenging. While substantial progress has been made in English, toxicity detection in

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation

arXiv:2602.09130v3 Announce Type: replace Abstract: Model compression is increasingly essential for deploying large language models (LLMs), yet existing comparative studies largely focus on pruning an

Vision-Braille: A Curriculum Learning Toolkit and Braille-Chinese Corpus for Braille Translation

arXiv:2407.06048v2 Announce Type: replace Abstract: We present Vision-Braille, the first publicly available end-to-end system for translating Chinese Braille extracted from images into written Chinese

applicationsarxiv-cs-cl

Agents

We are entering an extremely exciting era for open-weight models. Kimi K2.6 now feels like a top agentic model. I took it for a spin via @Fi…

We are entering an extremely exciting era for open-weight models. Kimi K2.6 now feels like a top agentic model. I took it for a spin via @FireworksAI_HQ fast inference APIs. Kimi K2.6 has impressive a

agentsdair-ai--x

What makes an entity salient in discourse?

arXiv:2508.16464v2 Announce Type: replace Abstract: Entities in discourse vary in salience: main participants, objects and locations stay prominent, while others are quickly forgotten, raising questio

Who is the richest club in the championship? Detecting and Rewriting Underspecified Questions Improve QA Performance

arXiv:2602.11938v5 Announce Type: replace Abstract: Large language models (LLMs) perform well on well-posed questions, yet standard question-answering (QA) benchmarks remain far from solved. We argue

XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants

model-releasesarxiv-cs-lg

arXiv:2503.14281v4 Announce Type: replace-cross Abstract: AI coding assistants are widely used for tasks like code generation. These tools now require large and complex contexts, automatically sourced

Tutorials

A Case Study on the Impact of Anonymization Along the RAG Pipeline

arXiv:2604.15958v1 Announce Type: cross Abstract: Despite the considerable promise of Retrieval-Augmented Generation (RAG), many real-world use cases may create privacy concerns, where the purported u

tutorialsarxiv-cs-cl

A Systematic Study of Training-Free Methods for Trustworthy Large Language Models

arXiv:2604.15789v1 Announce Type: new Abstract: As Large Language Models (LLMs) receive increasing attention and are being deployed across various domains, their potential risks, including generating

Adaptive multi-fidelity optimization with fast learning rates

arXiv:2604.16239v1 Announce Type: cross Abstract: In multi-fidelity optimization, biased approximations of varying costs of the target function are available. This paper studies the problem of optimiz

Aerial Multi-Functional RIS in Fluid Antennas-Aided Full-Duplex Networks: A Self-Optimized Hybrid Deep Reinforcement Learning Approach

arXiv:2604.14309v2 Announce Type: replace-cross Abstract: To address high data traffic demands of sixth-generation (6G) networks, this paper proposes a novel architecture that integrates autonomous ae

safetyarxiv-cs-ai

AHS: Adaptive Head Synthesis via Synthetic Data Augmentations

arXiv:2604.15857v1 Announce Type: new Abstract: Recent digital media advancements have created increasing demands for sophisticated portrait manipulation techniques, particularly head swapping, where

applicationsarxiv-cs-cv

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Analysis

model-releasesarxiv-cs-ai

arXiv:2604.16205v1 Announce Type: cross Abstract: Computational X-ray absorption near-edge structure (XANES) is widely used to probe local coordination environments, oxidation states, and electronic s