Search: “model-releases”

Passing Coarse Marginal Checks Can Be Cheap: Persona Mixtures and Imprecise Treatment-Response Estimates in an LLM Persona Panel

arXiv:2608.00979v1 Announce Type: cross Abstract: Large language models are increasingly used as synthetic research participants and are often validated by whether their marginal responses resemble hu

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Model Releases

PhysAgent: A Multi-Agent Framework for Reliable Remote Heart Rate Estimation

DGX agent

arXiv:2608.00066v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact heart-rate estimation from facial videos, but its weak physiological signal is easily corrupted b

model-releasesarxiv-cs-cv

4 Aug 2026

PNEC-Mamba: Prototype-Guided Positive-Negative Evidence Calibration for Hyperspectral Image Classification

arXiv:2608.01910v1 Announce Type: new Abstract: In real-world hyperspectral scenes, pixel representations are often ambiguous due to factors such as spectral similarity, mixed pixels, and local contex

PredAct-Bench: Benchmarking Tool-Augmented Dialogue under Controlled Tool Noise

arXiv:2608.02372v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in task-oriented dialogue systems that support multi-step decision-making in high-stakes domains

Private Generative Bootstrap via Blocking

arXiv:2608.02480v1 Announce Type: cross Abstract: With AI systems gaining more access to individuals' information, it is important to protect privacy when reporting statistical answers. Equally import

Prompt-Induced Waste in Large Reasoning Models: A Preregistered Two-Harness Benchmark of Coding Agents

arXiv:2608.01347v1 Announce Type: new Abstract: Large reasoning models used as coding agents incur costs from deliberation, tool calls, and repeated agent turns, yet the causal effect of prompt wordin

Protocol generalisation for brain tissue microstructure estimation via hypernetwork-controlled geometric deep learning

arXiv:2608.02053v1 Announce Type: cross Abstract: Brain tissue microstructure estimation with machine learning provides higher computational efficiency than conventional fitting. However, machine lear

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models

arXiv:2506.07121v2 Announce Type: replace Abstract: Ensuring the safety and robustness of large language models (LLMs) is a fundamental challenge and a critical prerequisite for the responsible deploy

QuerySplat: Decoupling Geometry and Appearance Representations in 3DGS Prediction

arXiv:2608.01186v1 Announce Type: new Abstract: While feed-forward 3D Gaussian Splatting (3DGS) enables efficient 3D reconstruction, achieving high-fidelity rendering remains challenging. Existing pix

Qwen-CUA: Native Computer Use for (almost) Everything

arXiv:2608.02352v1 Announce Type: cross Abstract: Native computer use offers a general interface for agents to operate almost any software available to people, but requires long-horizon state tracking

RamanPFN: learning from Raman spectral structure with a tabular foundation model

arXiv:2608.02157v1 Announce Type: new Abstract: Raman spectroscopy enables non-destructive, label-free molecular characterization across materials science, biomedicine and process monitoring. Predicti

Ranking Image Fusion the Way Humans Do: A Learned Pairwise Preference Metric for Infrared-Visible Fusion Assessment

arXiv:2608.01301v1 Announce Type: new Abstract: Infrared-visible image fusion (IVIF) has no ideal fused reference, so fusion algorithms are routinely ranked by scalar objective metrics that formalize

RAP: KV-Cache Compression via RoPE-Aligned Pruning

arXiv:2602.02599v4 Announce Type: replace Abstract: Long-context inference in large language models (LLMs) is bottlenecked by the memory and compute of the key-value (KV) cache. Structured pruning is

Real-Time Detection and Repair of LLM Agent Failures

arXiv:2608.02464v1 Announce Type: cross Abstract: LLM agents fail mid-episode -- they loop, cascade tool errors, drift off goal, fabricate results, or silently absorb corrupted content -- and the stan

Real-Time Visual Obstruction Detection in Surgical Augmented Reality

arXiv:2608.00232v1 Announce Type: new Abstract: Surgical augmented reality (AR) can provide contextual guidance by overlaying virtual annotations, tool cues, and procedural information onto the surgic

ReasonCast: Towards Explainable Time Series Forecasting with Reasoning

arXiv:2608.01875v1 Announce Type: cross Abstract: Most time series (TS) models are specialized for a single task, either understanding (i.e., returning text answers about a TS) or generation (i.e., re

Recursive Vision Language Models for General Symbolic Reasoning

arXiv:2608.01534v1 Announce Type: new Abstract: Hard symbolic-reasoning tasks such as Sudoku, maze pathfinding, and ARC remain challenging for LLMs due to their fixed-depth autoregressive reasoning, w

Refine Drugs, Don't Complete Them: Uniform-Source Discrete Flows for Fragment-Based Drug Discovery

arXiv:2509.26405v2 Announce Type: replace Abstract: We introduce InVirtuoGen, a discrete flow generative model for fragmented SMILES for de novo and fragment-constrained generation, and target-propert

REFLEX: Rethinking MoE Inference as Refinement-Aware Compute Allocation in Diffusion Language Models

arXiv:2608.01784v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models increase parameter capacity by activating only a small subset of experts for each token. This conditional-computation

Relative Parameter Importance in Task-Agnostic Replay-Free Continual Learning

arXiv:2608.00630v1 Announce Type: new Abstract: Achieving continual learning (CL) with deep neural networks requires balancing stability and plasticity while enabling knowledge transfer. In this work,

Relax Within, Balance Across: Geometry-Guided Load Balancing for Vision-Language Mixture-of-Experts

arXiv:2608.00574v1 Announce Type: new Abstract: Vision-language MoE batches contain different numbers of image and text tokens. Image resolution, image count, tiling, and prompt length all change this

Residual-Based Adaptive Kalman Filtering for Legged Robot State Estimation

model-releasesarxiv-cs-ro

arXiv:2608.02316v1 Announce Type: new Abstract: State estimation is a key component in model-based control of walking robots and, more broadly, applicable wherever hidden variables must be inferred. T

Response Magnitude as a Dominant Signal for Held-Out CRISPRi Perturbation Effect Prediction

arXiv:2608.00152v1 Announce Type: new Abstract: Predicting the magnitude of a CRISPRi perturbation's transcriptomic effect on held-out target genes is an important open problem in single-cell biology.

RestoreKV: Recovering Full-Cache Behavior Under Aggressive Query-Agnostic KV Cache Eviction

arXiv:2608.01247v1 Announce Type: new Abstract: Query-agnostic KV cache eviction compresses a context once and reuses the resulting cache for arbitrary future queries, but performance can collapse und

Rethinking Federated Graph Foundation Models: A Graph-Language Alignment-based Approach

arXiv:2601.21369v2 Announce Type: replace Abstract: Recent studies of federated graph foundational models (FedGFMs) break the idealized and untenable assumption of having centralized data storage to t

Reusing Rollouts under Policy Lag: Prefix-Normalized Policy Optimization for LLM Reinforcement Learning

arXiv:2608.01418v1 Announce Type: cross Abstract: Autoregressive rollout generation is a major computational cost in reinforcement learning for large language models. Reusing each rollout batch for ad

Riemannian Attention Mechanisms for Transformers: A Theoretical Framework and Architecture Design

arXiv:2608.01283v1 Announce Type: new Abstract: All Transformer-based large language models compute attention via the Euclidean inner product, an architectural choice that Dong et al. (2021) proved ca

Right Answer, Wrong Method: Shortcut Hacking Misleads the Evaluation of LLM Reasoning on Frontier Science Benchmarks

arXiv:2608.02442v1 Announce Type: cross Abstract: Scientific reasoning benchmarks typically evaluate large language models (LLMs) using final-answer accuracy. However, a correct answer does not necess

RING: Retrieval-Internalized Generation for Continual Large-Scale Knowledge Injection

arXiv:2608.01630v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves factuality but adds latency and engineering overhead at serving time. We propose RING (Retrieval-Internali

RIT*: Riemannian Informed Trees for Cost-Adaptive Optimal Motion Planning

model-releasesarxiv-cs-ro

arXiv:2608.00822v1 Announce Type: new Abstract: We present Riemannian Informed Trees (RIT*), a planning framework that replaces Euclidean primitives in batch-informed search with their Riemannian coun

Robust Watermarks Meet Backdoored Models: Evading Diffusion Semantic Watermarks via Stealthy Backdoor

arXiv:2608.00543v1 Announce Type: cross Abstract: Although semantic watermarking is considered a promising safeguard for images generated by Latent Diffusion Models (LDMs), the reliance of the waterma

Role Steering of Language Models for Social Simulations

arXiv:2608.00023v1 Announce Type: new Abstract: Social simulations built from language-model agents need role-conditioned behavior that can be checked before agents are placed into a simulated populat

Round-Trip Consistency: Bidirectional Diffusion Models Can Predict Their Own Rollout Errors

arXiv:2608.00675v1 Announce Type: cross Abstract: Autoregressive models accumulate error over long rollouts, yet at deployment there is no ground truth to measure it against. We train a single conditi

RSC-GestureNet: Reliability-Aware Selective Causal Recognition of Chinese Traffic Police Gestures

arXiv:2608.02200v1 Announce Type: new Abstract: Traffic police gestures are safety-critical perception cues for autonomous driving. A deployable recognizer must infer commands causally from continuous

RSRA: Training-Free Probing of Representation Sensitivity for Efficient LoRA Rank Allocation

arXiv:2607.09757v2 Announce Type: replace Abstract: Parameter-efficient fine-tuning enables large language models to adapt to downstream tasks with substantially lower computational and storage cost,

RSVideo: Are Your Vision-Language Models Ready for Remote Sensing Videos?

arXiv:2608.02039v1 Announce Type: new Abstract: Remote-sensing videos enable real-time observation of changes in target attributes, short-term activities, and scene evolution. They record motion, acti

S^4R: Selective Sampling, Subspaces, and Sparse Reconstruction for Compressed Long-Context KV Caching

arXiv:2608.00528v1 Announce Type: new Abstract: The growth of context window lengths in Large Language Models (LLMs) significantly enhances their long-context capabilities but incurs prohibitive memor

SAFE-Merge: Data-Free Continual Model Merging with General Knowledge Preservation

arXiv:2608.01184v1 Announce Type: new Abstract: Data-free continual model merging must incorporate a stream of specialized models while retaining both pretrained general knowledge and previously acqui

SafeBuild-Bench: A Temporal-Robust Construction Safety Benchmark with Graph-Enhanced Data Mining

arXiv:2608.00068v1 Announce Type: new Abstract: Construction-safety models must handle concrete deployment risks, such as a worker standing near a scaffold edge without guardrails, rather than only re

SCHEDBench: A Benchmark for Evaluating LLM Constraint Faithfulness in Natural-Language Combinatorial Scheduling

arXiv:2608.00991v1 Announce Type: cross Abstract: This paper introduces SCHEDBench, a natural-language benchmark for evaluating combinatorial scheduling constraint faithfulness under surface-form vari

SCOPE: Entanglement Frontier Escape for Source-Free Class Unlearning

arXiv:2608.02058v1 Announce Type: new Abstract: Source-free class unlearning erases whole classes using only the forget data, judged at the representation level, where features can leak a class the he

ScrambleToolBench: Agents Search Exhaustively Even When Their Own Map Points to the Next Step

arXiv:2608.02358v1 Announce Type: new Abstract: To operate robustly in open-world environments, autonomous agents should be able to infer the behavior of unfamiliar systems through interaction alone,

Self-composing neural operators for high-frequency and multiscale PDE surrogates

arXiv:2508.20650v2 Announce Type: replace Abstract: Addressing the computational challenges of high-frequency and multiscale partial differential equations (PDEs), this work introduces a self-composin

Semantic-Guided Cross-Sensor Super Resolution of Remote Sensing Images: A Gated Dual Conditioning Flow Matching Model

arXiv:2510.23816v3 Announce Type: replace Abstract: High spatial resolution satellite imagery is critical for monitoring fine-scale Earth surface processes, but is often limited by cost and revisit ti

SERL-SQL: Selective Hindsight Distillation for Text-to-SQL Reinforcement Agentic Learning

arXiv:2608.00485v1 Announce Type: new Abstract: Recent Text-to-SQL systems increasingly rely on multi-turn interaction, execution feedback, and reinforcement learning. However, most existing methods u

Similarity-Aware Machine Unlearning

arXiv:2608.00246v1 Announce Type: new Abstract: Machine unlearning removes the influence of user-specified training examples from a trained model, avoiding the need to retrain it from scratch. Localiz

Simulation-Based Plate-Reverb Parameter Estimation from a Single Impulse Response

arXiv:2608.00656v1 Announce Type: cross Abstract: We present a simulation-trained, non-iterative estimator for Task A of the 1st DAFx Parameter Estimation Challenge. Each unnormalized plate-reverb imp

SIPTraj: Map-Free End-to-End Trajectory Prediction via Physics-Guided Scene Interaction

model-releasesarxiv-cs-ro

arXiv:2608.00779v1 Announce Type: new Abstract: Trajectory prediction of surrounding agents is a prerequisite for safe planning and decision making in autonomous driving. Without high-definition (HD)