Search: “models”

Toward autocorrection of chemical process flowsheets using large language models

arXiv:2312.02873v2 Announce Type: replace-cross Abstract: The process engineering domain widely uses Process Flow Diagrams (PFDs) and Process and Instrumentation Diagrams (P&IDs) to represent process

safetyarxiv-cs-ai

9 Jun 2026

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Towards Long-Horizon Vessel Trajectory and Destination Forecasting with Reasoning Large Language Models

DGX agent

arXiv:2606.08633v1 Announce Type: new Abstract: Long-horizon maritime trajectory prediction is important for shipping management, logistics planning, and maritime risk analysis, yet month-level foreca

model-releasesarxiv-cs-ai

9 Jun 2026

Towards Mitigating Hallucinations in Large Vision-Language Models by Refining Textual Embeddings

arXiv:2511.05017v2 Announce Type: replace Abstract: Hallucinations in Large Vision-Language Models (LVLMs) remain a persistent challenge, often stemming from inadequate integration of visual informati

safetyarxiv-cs-cv

9 Jun 2026

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges

arXiv:2606.09125v1 Announce Type: cross Abstract: Privacy risks in text-only Large Language Models (LLMs) are well studied, particularly their tendency to memorize and leak sensitive information. Howe

researcharxiv-cs-ai

9 Jun 2026

Agents

Agentic Large Language Models for Automated Structural Analysis of 3D Frame Systems

arXiv:2606.06525v1 Announce Type: cross Abstract: Large language models (LLMs) have emerged as powerful foundation models with strong reasoning capabilities across domains. Beyond reactive text genera

agentsarxiv-cs-ai

Are Large Language Models Suitable for Graph Computation? Progress and Prospects

arXiv:2606.06865v1 Announce Type: new Abstract: Large language models (LLMs) have been increasingly explored for graph computation, where tasks require reasoning over structured relationships and algo

researcharxiv-cs-cl

Attention Consistent Longitudinal Medical Visual Question Answering Guided by Vision Foundation Models

model-releasesarxiv-cs-ai

arXiv:2606.06534v1 Announce Type: cross Abstract: Longitudinal medical visual question answering (VQA) requires reasoning about anatomical differences between an image of a current time point and an i

Agents

CRAFT: Coaching Reinforcement Learning Autonomously using Foundation Models for Multi-Robot Coordination Tasks

arXiv:2509.14380v3 Announce Type: replace Abstract: Multi-Agent Reinforcement Learning (MARL) provides a powerful framework for learning coordination in multi-agent systems. However, applying MARL to

agentsarxiv-cs-ro

Geometry of Semantic Space: Comparative Study of Discrete and Continuous Models

arXiv:2606.07183v1 Announce Type: new Abstract: This work examines the semantic geometry underlying NLP models. We compare supervised vector embeddings, such as CamemBERT, with lexical co-occurrence g

tutorialsarxiv-cs-cl

Interpreting Brain Responses to Language with Sparse Features from Language Models

arXiv:2606.06857v1 Announce Type: new Abstract: A central goal of cognitive neuroscience is to characterize the features that are represented by human language cortex. Artificial language models (LMs)

Learning Fair Demand Models

arXiv:2606.06830v1 Announce Type: cross Abstract: Data-driven pricing is increasingly prevalent in sectors such as airlines, lending, insurance, and retail. By learning demand models from customer fea

safetyarxiv-cs-lg

MedSIGHT: Towards Grounded Visual Comprehension in Medical Large Vision-Language Models

arXiv:2606.06760v1 Announce Type: new Abstract: Medical large vision-language models (Med-LVLMs) have recently achieved remarkable progress in vision-language comprehension and medical image segmentat

researcharxiv-cs-cv

OPTIMUS-Prime: Minimal and Sufficient Concept Explanations for Deep Vision Models

model-releasesarxiv-cs-cv

arXiv:2606.07180v1 Announce Type: new Abstract: The growing demand for transparency in automated decision-making has propelled eXplainable Artificial Intelligence (XAI) to the forefront of machine lea

TALAN: Task-Aligned Latent Adaptation Networks for Targeted Post-Training of Large Language Models

model-releasesarxiv-cs-lg

arXiv:2606.06902v1 Announce Type: new Abstract: Targeted post-training aims to improve reasoning, math, and code without degrading strengths. Low-rank adapters are efficient but task-global; activatio

The Lipreading Gap: Do VSR Models Perceive Visual Speech Like Human Lipreaders?

arXiv:2606.07435v1 Announce Type: cross Abstract: Visual speech recognition (VSR) models now surpass human lipreaders on benchmarks, but do such gains establish human-like visual speech perception? To

researcharxiv-cs-cl

Towards World Models in Biomedical Research

arXiv:2606.05925v1 Announce Type: new Abstract: A central goal of biomedicine is to understand, predict and ultimately control the dynamic mechanisms by which biological systems respond to perturbatio

safetyarxiv-cs-ai

6 Jun 2026

Local Ai

What options exist for running the largest local models at full precision?

local-air-stablediffusion

Running a 70B parameter model in full 16-bit precision requires roughly 140GB of memory , which is beyond most consumer hardware. Professional-tier GPUs like the RTX PRO 6000 with 96GB GDDR7 enable fu

6 Jun 2026

Benchmarking Open-Source Layout Detection Models for Data Snapshot Extraction from Institutional Documents

arXiv:2606.06242v1 Announce Type: new Abstract: Institutional documents contain substantial amounts of operational and analytical information embedded within figures and tables. Current approaches for

CLASH: Evaluating Language Models on Judging High-Stakes Dilemmas from Multiple Perspectives

arXiv:2504.10823v4 Announce Type: replace Abstract: Navigating dilemmas involving conflicting values is challenging even for humans in high-stakes domains, let alone for AI, yet prior work has been li

Global-Local Monte Carlo Tree Search in Vision-Language Models for Text-to-3D Indoor Scene Generation

arXiv:2606.06002v1 Announce Type: new Abstract: Large Vision-Language Models have achieved significant reasoning performance in various tasks.However, there are few studies on text-to-3D indoor scene

researcharxiv-cs-cv

Harnessing Structural Context for Entity Alignment Foundation Models

arXiv:2606.06109v1 Announce Type: new Abstract: Entity alignment (EA) aims to identify equivalent entities across heterogeneous knowledge graphs (KGs) and is a key component of knowledge fusion and cr

Learning Geometric Representations from Videos for Spatial Intelligent Multimodal Large Language Models

arXiv:2606.05833v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) excel at 2D semantic understanding but lack intrinsic 3D awareness, resulting in representations that fail to m

applicationsarxiv-cs-cv

Pitfalls of Evaluating Language Models with Open Benchmarks

arXiv:2507.00460v3 Announce Type: replace Abstract: Open Large Language Model (LLM) benchmarks, such as HELM and BIG-Bench, provide standardized and transparent evaluation protocols that support compa

3DThinkVLA: Endowing Vision-Language-Action Models with Latent 3D Priors via 3D-Thinking-Guided Co-training

arXiv:2606.04436v1 Announce Type: new Abstract: We propose a 3D-thinking-guided co-training framework that enables vision-language-action (VLA) models to perform 3D spatial reasoning implicitly during

applicationsarxiv-cs-cv

A real problem with feeling the acceleration viscerally is that current models are really good and it is hard to feel the vibe difference on…

applicationsethan-mollick--x

A real problem with feeling the acceleration viscerally is that current models are really good and it is hard to feel the vibe difference on most individual tasks with new models, even as AIs continue

Arithmetic Pedagogy for Language Models

arXiv:2606.05106v1 Announce Type: cross Abstract: We investigate whether methods of human mathematics pedagogy can guide the training of language models toward arithmetic reasoning. Building on the GA

tutorialsarxiv-cs-ai

BPDA-GMM: Bayesian Probabilistic Data Association via Gaussian Mixture Models for Semantic SLAM

model-releasesarxiv-cs-ro

arXiv:2606.04618v1 Announce Type: new Abstract: Probabilistic data association (PDA) improves semantic SLAM in perceptually aliased scenes, but existing methods often assume a fixed landmark set, reco

D^2SD: Accelerating Speculative Decoding with Dual Diffusion Draft Models

arXiv:2606.04446v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive large language model inference by drafting multiple tokens and verifying them in a single target-model

researcharxiv-cs-lg

Do Foundation Models See Biology? Evaluating Attention Coherence with Spatial Transcriptomics in Glioblastoma

arXiv:2606.04764v1 Announce Type: new Abstract: Whether attention maps from pathology foundation models capture genuine biology remains unknown, yet this question is critical for clinical trust and re

tutorialsarxiv-cs-cv

Folded Transport MCMC: Certifiable Quotient Posterior Computation for Symmetric Bayesian Models

arXiv:2606.04307v1 Announce Type: new Abstract: Bayesian models with finite symmetry - mixture models with exchangeable components, structural identification with closely-spaced modes - define posteri

researcharxiv-cs-lg

Imbuing Large Language Models with Bidirectional Logic for Robust Chain Repair

arXiv:2606.05030v1 Announce Type: new Abstract: Autoregressive chain-of-thought (CoT) reasoning in large language models (LLMs) is fundamentally forward-directed: each step conditions only on prior to

KODA: Contrastive Representation Comparison and Alignment for Vision-Language Foundation Models

arXiv:2606.04180v1 Announce Type: new Abstract: Vision-language foundation models such as CLIP and SigLIP provide widely used representations for multimodal learning systems. While these models are ty

safetyarxiv-cs-lg

Large Language Models Hack Rewards, and Society

arXiv:2606.04075v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a dominant post-training paradigm, enabling large language models (LLMs) to learn from rewards. We observe that

tutorialsarxiv-cs-ai

Large Language Models in K-12 Education: Alignment with State Curriculum Standards and Student Personas

arXiv:2606.04846v1 Announce Type: new Abstract: As Large Language Models (LLMs) become increasingly popular in educational settings, they raise important questions about the ethical implications of th

NextMotionQA: Benchmarking and Judging Human Motion Understanding with Vision-Language Models

arXiv:2606.04773v1 Announce Type: cross Abstract: Reliable evaluation of human motion understanding is fundamental to advancing embodied AI, robotics, and animation. However, existing benchmarks suffe

Reconciling Causality and Non-Equilibrium Thermodynamics with Hamiltonian Causal Models

arXiv:2606.04822v1 Announce Type: new Abstract: Causal modeling of physical temporal phenomena must handle interventions that act along trajectories, nonstationary induced laws, path-dependent effects

applicationsarxiv-cs-lg

Local Ai

Recover-LoRA for Aggressive Quantization: Reclaiming Accuracy in 2-Bit Language Models via Low-Rank Adaptation with Knowledge Distillation on Synthetic Data

arXiv:2606.04238v1 Announce Type: cross Abstract: Aggressive weight quantization to 2-bit precision offers substantial throughput and memory gains for large language model (LLM) inference, but typical

local-aiarxiv-cs-ai

reiterating: 'We're using the more expensive models to explore. Once we scale some of these experiences, we'll look to bring in more efficie…

applicationsclem-delangue--x

reiterating: 'We're using the more expensive models to explore. Once we scale some of these experiences, we'll look to bring in more efficient models that are more efficient on a token basis or are op

Selecting haptic guidance models in teleoperation: guidelines from a comparative user study

arXiv:2606.04157v1 Announce Type: new Abstract: Haptic guidance in teleoperation enhances operator performance through force feedback. This paper presents guidelines to select the most appropriate mod

researcharxiv-cs-ro

SMAC-Talk: A Natural Language Extension of the StarCraft Multi-Agent Challenge for Large Language Models

model-releasesarxiv-cs-ai

arXiv:2606.04202v1 Announce Type: new Abstract: As LLMs become more widely deployed, they are increasingly expected to work alongside other AI agents rather than operating in isolation. Effective coor

Toward Trustworthy Portrait Editing: Evaluation of Demographic Misrepresentation in I2I Models

model-releasesarxiv-cs-cv

arXiv:2602.16149v2 Announce Type: replace Abstract: Instruction-guided image-to-image (I2I) editors are increasingly used in consumer and professional visual workflows, where trustworthiness depends n

Clustered Self-Assessment: A Simple yet Effective Method for Uncertainty Quantification in Large Language Models

arXiv:2606.03846v1 Announce Type: cross Abstract: Large language models (LLMs) demonstrate remarkable performance across diverse tasks, but they often generate responses that appear plausible while be

researcharxiv-cs-ai

Fully Automated Identification of Lexical Alignment and Preference-Stage Shifts in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2606.03165v1 Announce Type: cross Abstract: The language used by digital chat assistants such as ChatGPT can diverge from human expectations (misalignment). Research, mostly on Scientific Englis

Local Ai

Neural Fields as World Models

arXiv:2602.18690v2 Announce Type: replace-cross Abstract: Humans rehearse possible futures offline, as in mental practice and perhaps dreaming, suggesting that world models may support task learning a

local-aiarxiv-cs-cv

Agents

PHASER: Phase-Aware and Semantic Experience Replay for Vision-Language-Action Models

arXiv:2606.03598v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have achieved remarkable success in language-conditioned robotic manipulation. However, deploying these models in

agentsarxiv-cs-ai

PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization

arXiv:2606.03444v1 Announce Type: cross Abstract: Unifying the complementary strengths of diverse Vision Foundation Models (VFMs) into a single efficient model is highly desirable but challenged by th

researcharxiv-cs-ai

Quantifying Faithful Confidence Expression in Large Reasoning Models

arXiv:2606.03969v1 Announce Type: cross Abstract: Reliable uncertainty communication is critical to the trustworthiness of LLMs, yet faithful calibration (FC)--the alignment between models' intrinsic

safetyarxiv-cs-ai

Routing and post-training open-source models won't only give you more accurate systems but also meaningfully faster and cheaper systems as m…

applicationsclem-delangue--x

Routing and post-training open-source models won't only give you more accurate systems but also meaningfully faster and cheaper systems as most companies are currently learning (in addition to giving