REVIEW 16 cited by
Empower Entity Set Expansion via Language Model Probing
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
read the original abstract
Entity set expansion, aiming at expanding a small seed entity set with new entities belonging to the same semantic class, is a critical task that benefits many downstream NLP and IR applications, such as question answering, query understanding, and taxonomy construction. Existing set expansion methods bootstrap the seed entity set by adaptively selecting context features and extracting new entities. A key challenge for entity set expansion is to avoid selecting ambiguous context features which will shift the class semantics and lead to accumulative errors in later iterations. In this study, we propose a novel iterative set expansion framework that leverages automatically generated class names to address the semantic drift issue. In each iteration, we select one positive and several negative class names by probing a pre-trained language model, and further score each candidate entity based on selected class names. Experiments on two datasets show that our framework generates high-quality class names and outperforms previous state-of-the-art methods significantly.
Forward citations
Cited by 16 Pith papers
-
NavVerse: Benchmarking Indoor-to-Outdoor Embodied Navigation in Continuous Robot Simulation
A new physics-enabled benchmark with 10,000 indoor, outdoor, and indoor-to-outdoor navigation episodes shows current zero-shot agents fail most when crossing the indoor-outdoor boundary, especially on the new PlaceNav task.
-
Geometrically Approximated Modeling for Emitter-Centric Ray-Triangle Filtering in Arbitrarily Dynamic LiDAR Simulation
GRCA uses emitter-centric geometric culling of rays per triangle to accelerate LiDAR simulation in arbitrarily dynamic scenes, reporting up to 14.55x speedup over Embree and 7.97x over OptiX.
-
IcFuzz: Fuzzing Isaac Sim with Semantic Stage Guidance and Multi-level Mutation
IcFuzz, an LLM-guided fuzzer for Isaac Sim, reaches about double the code coverage of prior baselines and has found 11 bugs, 9 confirmed or fixed.
-
Omni-Perception: Omnidirectional Collision Avoidance for Legged Locomotion in Dynamic Environments
Omni-Perception is an end-to-end RL policy for legged robots that processes raw LiDAR point clouds with PD-RiskNet to achieve omnidirectional collision avoidance, validated in simulation and on a Unitree G1.
-
Curio: A Cost-Effective Solution for Robotics Education
A below-$50 smartphone-powered robot using web-based control was tested with 20 students, who self-reported high engagement and improved robotics understanding.
-
Mesh2SLAM in VR: A Fast Geometry-Based SLAM Framework for Rapid Prototyping in Virtual Reality Applications
Mesh2SLAM projects known mesh vertices into the camera as features, enabling real-time mapping and tracking inside VR headsets with higher speed and lower error than image-based ORB-SLAM2 in virtual scenes.
-
When Uncertainty Leads to Unsafety: Empirical Insights into the Role of Uncertainty in Unmanned Aerial Vehicle Safety
Analyzing about 5,000 simulated drone flights shows that up to 89% of unsafe states are preceded by erratic control decisions, and an autoencoder on heading angle detects this uncertainty with up to 96% precision.
-
LOTUSim: Multi-Domain Simulator for Marine Robotics
LOTUSim delivers real-time multi-user HITL simulation of heterogeneous maritime fleets plus an Ekman-layered current model that substantially reduces error versus Gauss–Markov baselines.
-
A Physics-Based Continuum Model for Versatile, Scalable, and Fast Terramechanics Simulation
Chrono::CRM is an open-source SPH continuum terramechanics solver validated against cratering, cone penetration, and NASA rover tests, with near-real-time speeds and multi-kilometer terrain scaling.
-
HMR-ODTA: Online Diverse Task Allocation for a Team of Heterogeneous Mobile Robots
HMR-ODTA, an auction-based scheduler with temporal-network-based rescheduling, is claimed to reduce penalties by about 50% to 63% over prior methods in simulated hospital deliveries.
-
Re$^3$Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation
A reconstruction and neural-rendering pipeline converts real tabletop scenes into photorealistic robot simulations, and policies trained only on simulated data transfer zero-shot to the real robot with an average succ...
-
Exploring the Implicit Semantic Ability of Multimodal Large Language Models: A Pilot Study on Entity Set Expansion
LUSAR applies listwise sampling and ranking to multimodal LLMs for entity set expansion and reports improved MESED scores, though the gains are confounded with supervised fine-tuning.
-
Model-Based Systems Engineering Framework for SysML-Driven Design of Autonomous UAVs
A design-phase SysML-to-ROS 2 framework for autonomous UAVs ties requirements, functions, logical architecture, and planned software interfaces into one traceable model, with validation still pending.
-
Trajectory Adaptation using Large Language Models
A prompt-engineering pipeline in which an LLM produces a high-level plan and Python code that adapts precomputed robot waypoints to natural language commands, demonstrated in simulation.
-
Scalable and low-cost remote lab platforms: Teaching industrial robotics using open-source tools and understanding its social implications
Two open-source remote lab architectures (VPN-only and VNC-plus-VPN) let thousands of students practice industrial robotics on real hardware, but evidence of learning effectiveness is mostly task completion and self-reports.
-
Verification and Validation of a Vision-Based Landing System for Autonomous VTOL Air Taxis
Using Verse and CARLA, the authors compute reachable sets for a simulated VTOL landing system and claim safe landing within a helipad and collision avoidance in five scenarios.
Discussion (0). Continue with ORCID to comment.