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Do Better Goal Representations Improve Goal-Conditioned Reinforcement Learning?

arXiv:2609.39901v1 Announce Type: cross Abstract: Goal-conditioned reinforcement learning (GCRL) relies heavily on how target goals are represented to the policy. While recent methods encode goals via

Agents

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Do Self-Evolving Skills Generalize to Held-Out Tasks?

DGX agent

arXiv:2609.39148v1 Announce Type: new Abstract: AI agents can externalize what they learn from past tasks into reusable skills, such as procedures, checklists, code, or other executable artifacts, tha

agentsarxiv-cs-ai

1 Oct 2026

Doc2LoRA Provides Decodable Representations of Scientific Ideas

arXiv:2609.38374v1 Announce Type: new Abstract: Representing scientific papers as points in a space lets us search for similar papers and inquire about how fields relate to one another and drive innov

researcharxiv-cs-cl

DODGER: Safety-Guided Reinforcement Learning for Robot Navigation Among Dynamic Obstacles

arXiv:2609.38873v1 Announce Type: new Abstract: Robots operating in human-centered environments must safely navigate among multiple dynamic obstacles to avoid collisions with people and surrounding in

Does a Shared Temperature Imply a Shared Angular Scale in Probabilistic Contrastive Learning?

arXiv:2609.38784v1 Announce Type: new Abstract: In probabilistic contrastive learning, a shared temperature is commonly interpreted as a shared similarity scale, but this interpretation does not hold

Does Gradient Conflict Predict the Understanding--Generation Trade-off? A Controlled Audit of Conflict-Metric Validity in Unified Multimodal Models

arXiv:2609.38465v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) are increasingly designed around gradient conflict between understanding and generation objectives. The premise that

Does Learning Protein Folding Generalize to Broader Reasoning?

arXiv:2609.38879v1 Announce Type: cross Abstract: Large language models rely heavily on human text, which often conveys surface answers rather than the spatial and structural logic behind them. Protei

Does Text Steer Neural PDE Surrogates? A Controlled Diagnostic with OperatorCLIP

arXiv:2609.38517v1 Announce Type: new Abstract: Lower error from a text-conditioned neural surrogate does not, by itself, show that the model uses the meaning of the text. We examine this attribution

safetyarxiv-cs-lg

Agents

Does This Action Still Explain the Task? Reverse Scoring for Diffusion Language Model Agents

arXiv:2609.38536v1 Announce Type: cross Abstract: Diffusion-based large language models (dLLMs) promise to break the sequential latency bottleneck of autoregressive agents through parallel decoding, b

agentsarxiv-cs-ai

DoGBench: Can Agents Meet Expert Standards for User-Facing Documentation?

arXiv:2609.39909v1 Announce Type: cross Abstract: We introduce DoGBENCH (Documentation Generation Benchmark), to our knowledge, the first benchmark for generating and maintaining real user-facing soft

Don't Inoculate Everything: Stratified Inoculation Prompting Narrows Backdoor Triggers and Preserves Desired Traits

arXiv:2609.35356v2 Announce Type: replace Abstract: Supervised fine-tuning can teach language models undesired behaviours alongside desired ones. Inoculation prompting (IP) aims to limit unwanted gene

Don't Repeat Yourself: Self-Supervised Fine-Tuning for Coverage

arXiv:2609.31688v2 Announce Type: replace Abstract: In verifiable domains such as math and coding, finding one correct solution among many attempts can matter more than the pass rate of each attempt.

researcharxiv-cs-cl

Applications

Draft: A Parametric Tool for Robot Design Exploration

arXiv:2609.38405v1 Announce Type: new Abstract: Robot performance is often limited by the cost of iterating on morphology and control together, since every computer-aided design (CAD) change has to be

applicationsarxiv-cs-ro

Drape-Compatible Tool-Tip Localization for Hand-Held Laparoscopic Instruments via UWB Carrier-Phase Ranging and Trocar-Constrained Geometry

arXiv:2609.39129v1 Announce Type: new Abstract: A surgical robot policy needs to know where each instrument's working end sits relative to the camera and to the other instrument, yet a laparoscopic op

Dream4ACT: A Shared Visual Action Interface for Multi-Embodiment Video-Action Modeling

arXiv:2609.40153v1 Announce Type: new Abstract: Video generation models (VGMs) offer strong spatiotemporal priors for embodied observation--action modeling. However, joint-space action vectors lack ex

researcharxiv-cs-ro

Drift Inspector: Exploring and Measuring Scientific Drift with Atomic Contribution Claims

model-releasesarxiv-cs-cl

arXiv:2609.39710v1 Announce Type: new Abstract: Scientific abstracts mix contributions with background, motivation, and meta-language, so tools that read them as-is cannot separate what a field produc

DrivingBench: Can Vision-Language Models Drive a Toyota Corolla?

arXiv:2609.38948v1 Announce Type: cross Abstract: Frontier models excel at many digital benchmarks, yet their ability to drive a real car, an everyday human skill, remains largely untested. We present

Drone Soccer: Learning to Manipulate with Multicopter Downwash

arXiv:2609.38588v1 Announce Type: new Abstract: Although multicopter drones are traditionally designed for 'perception-only' tasks, like mapping and exploration, recent work has sought to develop Unma

DSDyn-VLA: A Dual-Stream Dynamic Manipulation Framework with Motion Perception, Future Awareness, and Realtime Correction

model-releasesarxiv-cs-ro

arXiv:2609.39198v1 Announce Type: new Abstract: While Vision-Language-Action (VLA) models excel in static tasks, they struggle in dynamic environments where objects are in motion (e.g., conveyor belt

DualCast: A Dual-Path Language Model for Bimodal Financial Time-Series Forecasting

arXiv:2609.38197v1 Announce Type: cross Abstract: Financial time-series forecasting must capture price dynamics across heterogeneous assets while incorporating news available at prediction time. We in

DuplexAct-Bench: Broadening Full-Duplex Speech Evaluation toward Proactive Interaction across Diverse Behavioral Requirements

model-releasesarxiv-cs-cl

arXiv:2609.39446v1 Announce Type: new Abstract: Existing full-duplex speech benchmarks cover only subsets of real-time interaction behaviors, often under limited contextual conditions. We introduce Du

Hardware

DynaFlow: Transparent and Flexible Intra-Device Parallelism via Programmable Operator Scheduling

arXiv:2605.21603v1 Announce Type: cross Abstract: Intra-device parallelism addresses resource under-utilization in ML inference and training by overlapping the execution of operators with different re

hardwarearxiv-cs-lg

DynaHarness: A Dynamic Physical Harness for Self-Evolving Robot Agents

arXiv:2609.40306v1 Announce Type: cross Abstract: Pretrained robot policies provide useful action priors, but long-horizon manipulation still requires coordination between semantic reasoning and physi

Dynamic LoRA-Experts and Prototype-Ensemble Matching for Class-Incremental Learning

model-releasesarxiv-cs-lg

arXiv:2609.39839v1 Announce Type: new Abstract: Class-Incremental Learning (CIL) aims to continuously learn new classes without forgetting previously acquired knowledge. Parameter-efficient fine-tunin

Tutorials

Dynamics-Inspired Diffusion for Foreground-Preserving Document Background Editing

arXiv:2601.21857v2 Announce Type: replace Abstract: We revisit diffusion-based generation for structured visual content and identify a fundamental limitation of existing approaches: foreground preserv

tutorialsarxiv-cs-cv

Dynamics to decision: A mathematical theory of Lyapunov spectra and decision boundaries in deep classifiers

arXiv:2609.39190v1 Announce Type: new Abstract: A deep classifier is defined not only by the decision it produces, but also by the sequence of transformations through which that decision is formed. Tr

DyRAD: Radar Novel View Synthesis for Dynamic Driving Scenes

model-releasesarxiv-cs-cv

arXiv:2609.39841v1 Announce Type: new Abstract: Reconstructing dynamic driving scenes from recorded sensor data supports closed-loop evaluation of autonomous driving systems by synthesizing observatio

E2E-SWE: Benchmarking LLMs on Building Working Codebases from Scratch

arXiv:2609.38335v1 Announce Type: cross Abstract: Coding agents powered by large language models (LLMs) are evolving from making localized code changes to developing complete software repositories. Ho

ECHO-G: Embodied Co-speech Humanoid mOtion Generation

arXiv:2609.39575v1 Announce Type: cross Abstract: Generating full-body co-speech motion for humanoid robots requires coordinating speech prosody, linguistic content, and embodiment-specific motion. To

Hardware

EDGC: Entropy-driven Dynamic Gradient Compression for Efficient LLM Training

arXiv:2511.10333v2 Announce Type: replace-cross Abstract: Training large language models (LLMs) at scale incurs substantial communication overhead, while static gradient compression cannot adapt to gr

hardwarearxiv-cs-ai

Effective Does Not Mean Useful: Conditional Functional Substitutability for Redundancy and Scaling in Transformers

arXiv:2609.39259v1 Announce Type: new Abstract: Modern neural networks scale predictably, yet the mechanisms behind these regularities remain unclear. Neural redundancy is typically characterized by c

Effects of Structural Allocation of Geometric Task Diversity in Linear Meta-Learning Models

arXiv:2509.18349v4 Announce Type: replace-cross Abstract: Meta-learning aims to leverage information across related tasks to improve prediction on unlabeled data for new tasks when only a small number

EffGS: Efficient and High-Fidelity Gaussian Splatting

arXiv:2609.39553v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables real-time novel view synthesis, but existing general-purpose acceleration methods suffer severe rendering quality d

researcharxiv-cs-cv

Efficient Active Auditing of Multi-Group Fairness with Bias Probes

arXiv:2609.40034v1 Announce Type: cross Abstract: Over the past decade, Machine Learning (ML) has been trained under dual objectives: minimizing prediction error via Empirical Risk Minimization (ERM)

Hardware

Efficient Expert-Parallel Communication on PCIe-Connected Consumer GPUs

arXiv:2609.40093v1 Announce Type: cross Abstract: Expert parallelism (EP) enables inference of large Mixture-of-Experts (MoE) models by placing their experts across multiple GPUs, but requires substan

hardwarearxiv-cs-lg

Efficient Multi-Modal Planning with Reward-Guided Preference Optimization for Autonomous Driving

arXiv:2609.38862v1 Announce Type: cross Abstract: Safe and efficient trajectory planning is essential in autonomous driving. However, existing end-to-end approaches often fall short in both computatio

EFormer: Temporally Aligned Local Correction for Continuous sEMG-Based Hand Pose Tracking

model-releasesarxiv-cs-lg

arXiv:2609.38932v1 Announce Type: new Abstract: Surface electromyography (sEMG) provides a wearable, camera-free signal for continuous hand-motion inference. Mapping muscle activity to joint kinematic

Ego4WAM: What Matters When Scaling Egocentric Human Data for Robot Learning?

arXiv:2609.40341v1 Announce Type: cross Abstract: Egocentric human data provides a scalable source of experience for robot learning, but varies substantially in human-robot alignment, behavioral cover

safetyarxiv-cs-cv

EgoTools: Towards Tool-Centric Reasoning in Real-World Egocentric Videos

model-releasesarxiv-cs-cv

arXiv:2609.39378v1 Announce Type: new Abstract: Real-world embodied tasks, from everyday activities to professional procedures, require agents to act under physical constraints while tracking evolving

EHR-RobustGym: Benchmarking and Training Agents for Robust Clinical Reasoning

arXiv:2609.39371v1 Announce Type: new Abstract: In hospital workflows, electronic health records (EHRs) are often noisy, and may not contain the evidence needed to confirm events or measurements refer

EHR2Trace: Auditable EHR Data Infrastructure for Patient World Models and Clinical Agents

arXiv:2609.38193v1 Announce Type: cross Abstract: Patient world models and clinical agents aim to predict changes in patients' health and support clinical work. Developing these systems requires relia

Eigenism: Ethics for a Human-AI Future

arXiv:2606.12420v2 Announce Type: replace-cross Abstract: Our concepts of survival and self-interest were built for single, continuous biological lives. These ideas break down when applied to artifici

ElectrolyteFM: Unifying Electrolyte Property Prediction through Cross-Property Knowledge Learning

arXiv:2609.39340v1 Announce Type: new Abstract: Electrolyte formulation design requires balancing multiple physicochemical properties, yet existing models often focus on a limited subset. Learning eac

EmAvatar: Multimodal Empathetic Response Generation via Conflict Resolution and Expressive Guidance

model-releasesarxiv-cs-cv

arXiv:2609.38182v1 Announce Type: cross Abstract: Avatar-based multimodal empathetic response generation has emerged as a pivotal capability in human-centric systems, aiming to recognize user emotions

Embedding Physical Reasoning into Diffusion-Based Shadow Generation Under the Sun and Sky

arXiv:2512.06174v3 Announce Type: replace Abstract: Generating realistic cast shadows for inserted foreground objects requires reasoning about scene geometry and illumination. However, most learning-b

researcharxiv-cs-cv

Agents

Embodiment-aware control by inference over the operator: a simulation study

arXiv:2609.38437v1 Announce Type: new Abstract: Teleoperation systems are tuned for channel fidelity, while whether the operator experiences the device as part of the body, the Sense of Embodiment (So

agentsarxiv-cs-ro

EmbodiRSI: Recursive Self-Improvement for Data-Efficient Robot Adaptation

arXiv:2609.38905v1 Announce Type: new Abstract: Adapting robot manipulation policies to new tasks and environments remains highly data-intensive, while the data needed for further improvement depends

Emergent Multi-View Geometry Through Self-Distillation

arXiv:2609.39227v1 Announce Type: cross Abstract: Over a century ago, Henri Poincare argued that a motionless observer cannot acquire the notion of space. Yet, most visual representation learning meth