Search: “model-releases”

Assessing and Mitigating Miscalibration in LLM-Based Social Science Measurement

arXiv:2605.11954v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in social science as scalable measurement tools for converting unstructured text into variables t

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Model Releases

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics

DGX agent

arXiv:2507.21638v2 Announce Type: replace Abstract: The development of reinforcement learning (RL) algorithms has been largely driven by ambitious challenge tasks and benchmarks. Games have dominated

model-releasesarxiv-cs-ai

3 Jun 2026

ATLAS: A Large-Scale Evaluation Benchmark for Adversarial LiDAR Perception

arXiv:2606.02924v1 Announce Type: new Abstract: Autonomous driving perception is typically evaluated on clean benchmark data, yet real-world deployment requires robustness to rare, structured, and pot

Auditable Climate Risk Intelligence from Fragmented ESG Data: Deterministic Orchestration and Imbalance-Aware Learning for Scope 1-3 Validation

arXiv:2606.02604v1 Announce Type: cross Abstract: ESG and climate risk data remain fragmented across heterogeneous Scope 1, Scope 2, and Scope 3 reporting environments, while conventional validation p

AUDITFLOW: Executable Symbolic Environments for Structured Financial Reporting Verification

arXiv:2606.03031v1 Announce Type: new Abstract: Structured financial audit verification is difficult for language-model agents because correctness depends on structured evidence rather than text alone

Auditing Engagement Incentives in the Kidfluencer Ecosystem: A Multimodal Weak Supervision Approach

arXiv:2606.03173v1 Announce Type: cross Abstract: The rise of `kidfluencers' on YouTube has raised ethical concerns about child digital labor and exploitation. While emerging legislation attempts to r

AURA: Action-Gated Memory for Robot Policies at Constant VRAM

arXiv:2606.02775v1 Announce Type: new Abstract: The KV-cache is the right memory for datacenters but the wrong memory for robots. Datacenter inference batches many short requests and resets them, amor

Automated Report-Derived Oncology VQA Benchmark for Evaluating Vision-Language Models on 3D Medical Imaging

arXiv:2606.02809v1 Announce Type: new Abstract: Evaluating vision-language models (VLMs) on medical images requires benchmarks that are clinically grounded, scalable, and controlled for evaluation con

AVTrack: Audio-Visual Tracking in Human-centric Complex Scenes

arXiv:2606.02724v1 Announce Type: cross Abstract: Audio-visual speaker tracking aims to localize and track active speakers by leveraging auditory and visual cues, enabling fine-grained, human-centric

BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces

arXiv:2606.02798v1 Announce Type: new Abstract: Many decision-support settings require systems that adapt to individual users, but evaluation data for this problem remain limited. Existing benchmarks

Benchmarking Visual State Tracking in Multimodal Video Understanding

arXiv:2606.03920v1 Announce Type: new Abstract: Understanding a video requires more than recognizing isolated moments, as humans continuously track entities, states, and events over time. This capacit

BEV-ODOM2: Enhanced BEV-based Monocular Visual Odometry with PV-BEV Fusion and Dense Flow Supervision for Ground Robots

model-releasesarxiv-cs-ro

arXiv:2509.14636v2 Announce Type: replace Abstract: Scale-consistent ego-motion estimation is fundamental for autonomous ground robots. Bird's-Eye-View (BEV) representation naturally addresses the sca

Beyond Encoder Accumulation: Measuring Encoder Roles in Multi-Encoder VLMs

arXiv:2606.03879v1 Announce Type: cross Abstract: As foundation models scale toward fusing more heterogeneous visual streams, understanding how diverse encoders interact under joint training becomes a

Beyond Ideal Instruction: A Comprehensive Framework for Evaluating LLMs in Realistic Interactions

arXiv:2606.03318v1 Announce Type: new Abstract: Despite great advances in tool-use capabilities of large language models (LLMs), existing evaluation benchmarks struggle to fully align with real-world

BigFinanceBench: A Workflow-Grounded Benchmark for Financial-Research Agents

arXiv:2606.03829v1 Announce Type: new Abstract: Financial-research answers are decision-relevant only when another analyst can audit how they were produced: which source was chosen, which period and a

Calibration Data Trade-offs Across Capability Dimensions: Why Multi-Source Mixing Matters for High-Sparsity LLM Pruning

arXiv:2606.03328v1 Announce Type: cross Abstract: Post-training pruning compresses large language models to high sparsity using a small unlabelled calibration set, and recent work has concluded that t

Can Factual Opinions Be Edited (Manipulated) in Large Language Models?

arXiv:2606.03096v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly integrated into various domains, making knowledge editing techniques crucial yet potentially hazardous. Cu

Can Structural Cues Save LLMs? Evaluating Language Models in Massive Document Streams

arXiv:2603.19250v2 Announce Type: replace Abstract: Evaluating language models in streaming environments is critical, yet underexplored. Existing benchmarks either focus on single complex events or pr

CANMOT: Class-Aware Noise Modeling for Multi-Object Tracking in Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2606.03590v1 Announce Type: new Abstract: Kalman filter (KF)-based multi-object tracking (MOT) remains a strong baseline for autonomous driving due to its strong performance, computational effic

CAPER: Clause-Aligned Process Supervision for Text-to-SQL

arXiv:2606.03327v1 Announce Type: cross Abstract: Text-to-SQL systems are typically evaluated by query-level execution correctness, but this terminal signal provides little guidance about which interm

Causal Neural Probabilistic Circuits

arXiv:2603.01372v2 Announce Type: replace-cross Abstract: Concept Bottleneck Models (CBMs) enhance the interpretability of end-to-end neural networks by introducing a layer of concepts and predicting

Causal Preference Elicitation

arXiv:2602.01483v2 Announce Type: replace-cross Abstract: We propose causal preference elicitation, a Bayesian framework for expert-in-the-loop causal discovery that actively queries local edge relati

Characterizing Detectability in 3DGS Poisoning: A Stage-wise Benchmark

arXiv:2606.03499v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has rapidly emerged as a leading representation for real-time novel view synthesis, but recent work shows it is vulnerable

Chatbots Output Meaningful (but Problematic) Language

arXiv:2606.02973v1 Announce Type: new Abstract: Are utterances by AI chatbots meaningful? Concretely, if a user asks, say, Anthropic's agent Claude, 'What is the capital of Spain?' and Claude answers,

ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning

arXiv:2606.02802v1 Announce Type: new Abstract: Large language models (LLMs) exhibit strong natural-language reasoning abilities for clinical decision support, but struggle to effectively model struct

ClinicalMC: A Benchmark for Multi-Course Clinical Decision-Making with Large Language Models

arXiv:2606.03157v1 Announce Type: new Abstract: Large language models (LLMs) have been widely adopted in healthcare, yet they still encounter significant challenges in complex clinical decision-making

COD10K-C: Benchmarking Robustness of Camouflaged Object Detection Under Natural Image Corruptions

arXiv:2606.02603v1 Announce Type: new Abstract: Camouflaged object detection has improved substantially, but most standard benchmarks evaluate models only on clean images. This is not realistic becaus

CoEval: Ranking Language Models for Custom Tasks Without Labeled Data or Trustworthy Benchmarks

arXiv:2606.03650v1 Announce Type: cross Abstract: Choosing or ranking language models for a specific application is hardest when no task-specific labeled data exists, and standard public benchmarks ca

Coherent Swap Regret and Channel-Proof Learning

arXiv:2606.02655v1 Announce Type: cross Abstract: External regret certifies stability only against replacing one's behavior by a fixed alternative. In a quantum game, this misses a natural physical mo

Combining Statistical Features and Deep Encodings for Rehearsal-Based Class-Incremental Time Series Classification

arXiv:2606.03292v1 Announce Type: cross Abstract: Many systems used in real-world environments require adding new categories and incorporating new information without forgetting what was previously le

CoMPAS3D: A Dataset and Benchmark for Interactive Motion

arXiv:2507.19684v2 Announce Type: replace-cross Abstract: Socially interactive humanoid robots must engage with humans through their bodies, adapting in real time to a partner's movement, intent, and

Compress then Merge: From Multiple LoRAs into One Low-Rank Adapter

arXiv:2606.03723v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) enables parameter-efficient specialization of foundation models, but the proliferation of task-specific adapters fragments ca

Consistent Yet Wrong: Evidence Insensitivity in Spatial Vision-Language Models

arXiv:2606.02742v1 Announce Type: new Abstract: Spatial reasoning is fundamental to robotics, autonomy, and embodied AI, yet modern vision-language models (VLMs) remain unreliable on metric distance q

CoralBay: A Self-Supervised CT Foundation Model

arXiv:2606.03888v1 Announce Type: new Abstract: Self-supervised learning has enabled large-scale pre-training on 2D natural images, producing general-purpose visual representations that transfer effec

Cosmos 3: Omnimodal World Models for Physical AI

arXiv:2606.02800v1 Announce Type: cross Abstract: We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences

Cost-Aware Query Routing in RAG: Empirical Analysis of Retrieval Depth Tradeoffs

arXiv:2606.02581v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) faces a fundamental three-way tension: deeper retrieval improves factual grounding but inflates token costs and e

CourseTimeQA: A Lecture-Video Benchmark and a Latency-Constrained Cross-Modal Fusion Method for Timestamped QA

arXiv:2512.00360v2 Announce Type: replace Abstract: We study timestamped question answering over educational lecture videos under a single-GPU latency/memory budget. Given a natural-language query, th

CREward: A Type-Specific Creativity Reward Model

arXiv:2511.19995v2 Announce Type: replace Abstract: Creativity is a complex phenomenon. When it comes to representing and assessing creativity, treating it as a single undifferentiated quantity would

Critical evaluation of PINN for FWD inverse analysis and differentiable FEM as an alternative

arXiv:2606.03210v1 Announce Type: cross Abstract: Automatic-differentiation-based inverse analysis methods, including physics-informed neural networks (PINNs) and differentiable programming, have rece

Cross-Lingual Token Arbitrage: Optimizing Code Agent Context Windows via Local LLM Preprocessing

arXiv:2606.03618v1 Announce Type: new Abstract: AI-assisted coding agents are bottlenecked by input-token cost. Two pathologies of raw human input drive much of this overhead: tokenization inefficienc

Cryo-Bench: Benchmarking Foundation Models for Cryosphere Applications

arXiv:2603.01576v3 Announce Type: replace Abstract: Geo-Foundation Models (GFMs) have been evaluated across diverse Earth observation task including multiple domains and have demonstrated strong poten

DECA: Decentralizing Block-Wise Adam for Efficient LLM Full-Parameter Fine-Tuning on Non-IID Data

arXiv:2606.03209v1 Announce Type: new Abstract: Fine-tuning large language models (LLMs) in privacy-sensitive and resource-constrained environments remains challenging. Since training data are often d

Decoupled Smart Contract Audits: Lightweight LLM Framework via Distillation and Aggregation

arXiv:2606.03128v1 Announce Type: cross Abstract: Smart contracts face critical security challenges that require thorough auditing in decentralized web services. While Large Language Models (LLMs) hav

Demo2Tutorial: From Human Experience to Multimodal Software Tutorials

arXiv:2606.03951v1 Announce Type: new Abstract: Human experience in digital environments offers a vast, underexplored resource of authentic, untrimmed interactions that contain rich procedural knowled

DeskCraft: Benchmarking Desktop Agents on Professional Workflows and Human-in-the-Loop Collaboration

arXiv:2606.03103v1 Announce Type: new Abstract: Real-world professional desktop workflows in specialized creative and engineering software unfold over long horizons and often require human-in-the-loop

Diagnosing Knowledge Gaps in LLM Tool Use: An Agentic Benchmark for Novel API Acquisition

arXiv:2606.03657v1 Announce Type: new Abstract: Large language models for code generation often need to use APIs that are absent from their pretraining data. This requires more than recalling a functi

Diagnosis of Human Object Interaction Detectors for Real World Educational Applications

arXiv:2606.02789v1 Announce Type: new Abstract: Human-object interaction (HOI) recognition is critical for automatically analyzing student behavior in complex educational environments. Although state-

Disentangling Visual and Factual Correctness in LVLMs' Visualization Literacy

arXiv:2606.03142v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) show strong visualization interpretation, yet it is unclear whether their responses reflect genuine reasoning over