Views
No views yet
SentenceTransformer(
(0): Transformer({'max_seq_length': 384, 'do_lower_case': False, 'architecture': 'MPNetModel'})
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
(2): Normalize()
)pip install -U sentence-transformers1from sentence_transformers import SentenceTransformer
2
3# Download from the 🤗 Hub
4model = SentenceTransformer("sentence_transformers_model_id")
5# Run inference
6sentences = [
7 'Design of Digital Gloves with Feedback for VR',
8 'This article describes the first steps in the development of a lowcost digital sensory glove that designed for use in virtual reality systems especially Existing concepts of gloves differ in features and design they have various functions including feedback tactile feedback to the electric discharge a feeling of finger bending finger grip strength and prediction of action and threedimensional spatial positioning to improve sensation and practical experience in virtual reality Manual dynamic perception and freedom of action common in the real world provide instant information about objects in the virtual world Digital gloves act not only as a remote control in VR but also provide physical feedback for the user when they come in contact with virtual objects This article presented an own design for inexpensive gloves that allow for proximal and distal finger joint movements as well as positionorientation determination with an inertial measuring unit These sensors and tactile feedback caused by the vibration patterns of the coins at the fingertips are integrated into a wireless easytouse and opensource system The design of hardware as well as experiment plans for proof of concept is presented',
9 'Admission control in queuetime loop productionmixed integer programming with Lagrangian relaxation MIPLAR.Abstract Flow shop scheduling problems with queue time constraints abound in many types of industries. The waiting times between consecutive steps in flow shop production with queue time constraints cannot exceed a given interval. Typically managers use mixed integer linear programming MILP to schedule the process starting times of jobs in a queue. However as the number of jobs in the system increases the MILPbased model cannot return an optimal solution within a reasonable time because of its combinatorial nature. This paper proposes a mixed integer programming with Lagrangian relaxation MIPLAR method to solve the timeindexed MILP model with a separable structure for the production scheduling problem with queue time constraints. Lagrangian relaxation techniques are used to decompose the problem into joblevel subproblems which are solved by dynamic programming. The subgradient method is used to solve the Lagrangian dual problem. A 4.6month simulation study demonstrates that the proposed MIPLAR method improves the scrap count by a percentage range from 32.1 to 83.7 across the studied 16 scenarios compared to the firstinfirstout FIFO rule while maintaining the same range of the throughput.',
10]
11embeddings = model.encode(sentences)
12print(embeddings.shape)
13# [3, 768]
14
15# Get the similarity scores for the embeddings
16similarities = model.similarity(embeddings, embeddings)
17print(similarities)
18# tensor([[1.0000, 0.9487, 0.6646],
19# [0.9487, 1.0000, 0.6494],
20# [0.6646, 0.6494, 1.0000]])sentence1, sentence2, and label| sentence1 | sentence2 | label | |
|---|---|---|---|
| type | string | string | float |
| details |
|
|
|
| sentence1 | sentence2 | label |
|---|---|---|
A ManyObjective Particle Swarm Optimization Based On Virtual Pareto Front | A manyobjective problems MaOP refer to the optimization problem involving more than three objectives Particle swarm optimization PSO is one of the potential heuristic methods suited for solving MaOPs The personal best selection strategy the global best selection strategy and the archive maintenance strategy are the three key components in the design of a ManyObjective Particle Swarm Optimization MaOPSO The personal best and global best selection strategies determine the direction where particles will fly The archive maintenance strategy has an important impact on convergence and diversity of its algorithm In MaOPs the high dimensionality in the objective space decreases the probability of a solution to be dominated by the other solutions in the population Thus it becomes more difficult for PSO to select the good leaders from so many nondominated solutions In this paper a virtual Inverted Generational Distance indicator is proposed to evaluate the comprehensive quality of a solution in ... | 0.79 |
Multivision tracking and collaboration based on spatial particle filter | Abstract In existing multivision tracking methods a distributed collaborative tracking mode based on homography constraints is often adopted yet there are significant shortcomings to this approach For example visual information complementation is not used to improve the robustness of tracking and collaborative tracking is limited by homography constraints In this study a threedimensional spatial particle filter tracking method was proposed and multivision joint tracking and collaboration were effectively achieved This method was based on the existing particle filter framework A twodimensional plane particle was taken as the projection of a threedimensional spatial particle on the imaging plane and the formula for calculating a spatial particle’s weight was derived based on Bayesian posterior probability recursion In addition an approximation method to determine spatial particle weight was given The resampling of spatial particles was performed by using an epipolar line resampling metho... | 0.876 |
Incorporating Social Factors in Accessible Design.Personal technologies are rarely designed to be accessible to disabled people partly due to the perceived challenge of including disability in design. Through design workshops we addressed this challenge by infusing usercentered design activities with Design for Social Accessibilitya perspective emphasizing social aspects of accessibilityto investigate how professional designers can leverage social factors to include accessibility in design. We focused on how professional designers incorporated Design for Social Accessibilityu0027s three tenets 1 to work with users with and without visual impairments 2 to consider social and functional factors 3 to employ toolsa framework and method cardsto raise awareness and prompt reflection on social aspects toward accessible design. We then interviewed designers about their workshop experiences. We found DSA to be an effective set of tools and strategies incorporating socialfunctional and nondisabl... | Research on LC Filter Cascaded with Buck Converter Supplying Constant Power Load Based on IDAPassivityBased Control.Nowadays distribution power systems are used in different applications such as aircraft ships submarines and hybrid electric vehicles. However the interaction between individually designed power subsystems may cause instability. Moreover in these applications the constant power load CPL also poses challenges for system dynamic response and stability. Thus the main objective is to stabilize the cascaded system supplying the CPL. An interconnection and damping assignment IDA passivitybased control PBC scheme for LC filter cascaded with buck converter supplying CPL is proposed. The plant is described by portcontrolled Hamiltonian PCH form. Particularly an adaptive interconnection matrix is developed to achieve internal links in PCH system. A modified IDAPBC and its proof are presented to perfect the implementation for the CPL application. Simulation results are given to illu... | 0.107 |
CoSENTLoss with these parameters:
1{
2 "scale": 20.0,
3 "similarity_fct": "pairwise_cos_sim"
4}sentence1, sentence2, and label| sentence1 | sentence2 | label | |
|---|---|---|---|
| type | string | string | float |
| details |
|
|
|
| sentence1 | sentence2 | label |
|---|---|---|
Macroaware rowstyle power delivery network design for better routability | Reliability of a PG network is one of the most important concerns in a chip design which makes powerplanning the most critical step in the physical design Traditional PG network design mainly focuses on reducing usage of routing resource to satisfy voltage drop and electromigration constraints according to a regular mesh As the number of macros in a modern design increases this style may waste more routing resource and make routing congestion more severe in local regions In order to save routing resource and increase routability this paper proposes a delicate powerplanning method First we propose a rowstyle power mesh to facilitate connection of preplaced macros and increase routability of signal nets in the later stage Besides an effective power stripe width which can reduce wastage of routing resource and provide stronger supply voltage is found Moreover we propose the first work to use the linear programming algorithm to minimize PG routing area and consider routability at the same ... | 0.815 |
Haptic Codecs for the Tactile Internet | The Tactile Internet will enable users to physically explore remote environments and to make their skills available across distances An important technological aspect in this context is the acquisition compression transmission and display of haptic information In this paper we present the fundamentals and state of the art in haptic codec design for the Tactile Internet The discussion covers both kinesthetic data reduction and tactile signal compression approaches We put a special focus on how limitations of the human haptic perception system can be exploited for efficient perceptual coding of kinesthetic and tactile information Further aspects addressed in this paper are the multiplexing of audio and video with haptic information and the quality evaluation of haptic communication solutions Finally we describe the current status of the ongoing IEEE standardization activity P191811 which has the ambition to standardize the first set of codecs for kinesthetic and tactile information excha... | 0.93 |
Plosive voicing acoustics and voice quality in Yerevan Armenian.Abstract Yerevan Armenian is a variety of Eastern Armenian with a threeway voicing contrast that includes voiced voiceless unaspirated and voiceless aspirated stops but previous work has not converged on a description of how voice quality is involved in the contrast. We demonstrate how voice quality can be assessed in a twodimensional acoustic space using a spectral tilt measure in conjunction with a measure of spectral noise. Eight speakers produced a list of words with prevocalic wordinitial and postvocalic wordfinal plosives. The results suggest that Yerevan Armenian has breathyvoiced plosives which are produced with closure voicing and a relatively spread glottis that is maintained into a following vowel. These qualitatively differ from some Indic ones in that they do not have an extended interval of voiced aspiration after the closure. For the voiceless unaspirated plosives most speakers produced acoustically modal vo... | Analyzing the Error Propagation in a Parameterizable NetworkonChip Router.The constant reduction in the components size in integrated circuits and the increase of the operating frequency make SystemsonChip SoCs more vulnerable to noise and other interference phenomena. Such phenomena can lead to faults which generate errors that may result in a system crash. SoCs with dozens of cores use NetworksonChip as their interconnection architecture. In this context this work presents an analysis of the error propagation in a parameterizable router architecture that allows different combinations of input and output controllers data width and buffers depth. The router has been described focusing on design flexibility and low logical resource occupation. We elaborated different combinations of the router architecture and evaluated the error propagation by means of Single Event Upset fault injections. The synthesis results presented a reasonable increase in term of logical elements when applying wi... | 0.138 |
CoSENTLoss with these parameters:
1{
2 "scale": 20.0,
3 "similarity_fct": "pairwise_cos_sim"
4}eval_strategy: stepsper_device_train_batch_size: 128per_device_eval_batch_size: 16num_train_epochs: 1warmup_ratio: 0.1fp16: Truebatch_sampler: no_duplicatesoverwrite_output_dir: Falsedo_predict: Falseeval_strategy: stepsprediction_loss_only: Trueper_device_train_batch_size: 128per_device_eval_batch_size: 16per_gpu_train_batch_size: Noneper_gpu_eval_batch_size: Nonegradient_accumulation_steps: 1eval_accumulation_steps: Nonetorch_empty_cache_steps: Nonelearning_rate: 5e-05weight_decay: 0.0adam_beta1: 0.9adam_beta2: 0.999adam_epsilon: 1e-08max_grad_norm: 1.0num_train_epochs: 1max_steps: -1lr_scheduler_type: linearlr_scheduler_kwargs: {}warmup_ratio: 0.1warmup_steps: 0log_level: passivelog_level_replica: warninglog_on_each_node: Truelogging_nan_inf_filter: Truesave_safetensors: Truesave_on_each_node: Falsesave_only_model: Falserestore_callback_states_from_checkpoint: Falseno_cuda: Falseuse_cpu: Falseuse_mps_device: Falseseed: 42data_seed: Nonejit_mode_eval: Falseuse_ipex: Falsebf16: Falsefp16: Truefp16_opt_level: O1half_precision_backend: autobf16_full_eval: Falsefp16_full_eval: Falsetf32: Nonelocal_rank: 0ddp_backend: Nonetpu_num_cores: Nonetpu_metrics_debug: Falsedebug: []dataloader_drop_last: Falsedataloader_num_workers: 0dataloader_prefetch_factor: Nonepast_index: -1disable_tqdm: Falseremove_unused_columns: Truelabel_names: Noneload_best_model_at_end: Falseignore_data_skip: Falsefsdp: []fsdp_min_num_params: 0fsdp_config: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}fsdp_transformer_layer_cls_to_wrap: Noneaccelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}parallelism_config: Nonedeepspeed: Nonelabel_smoothing_factor: 0.0optim: adamw_torch_fusedoptim_args: Noneadafactor: Falsegroup_by_length: Falselength_column_name: lengthddp_find_unused_parameters: Noneddp_bucket_cap_mb: Noneddp_broadcast_buffers: Falsedataloader_pin_memory: Truedataloader_persistent_workers: Falseskip_memory_metrics: Trueuse_legacy_prediction_loop: Falsepush_to_hub: Falseresume_from_checkpoint: Nonehub_model_id: Nonehub_strategy: every_savehub_private_repo: Nonehub_always_push: Falsehub_revision: Nonegradient_checkpointing: Falsegradient_checkpointing_kwargs: Noneinclude_inputs_for_metrics: Falseinclude_for_metrics: []eval_do_concat_batches: Truefp16_backend: autopush_to_hub_model_id: Nonepush_to_hub_organization: Nonemp_parameters:auto_find_batch_size: Falsefull_determinism: Falsetorchdynamo: Noneray_scope: lastddp_timeout: 1800torch_compile: Falsetorch_compile_backend: Nonetorch_compile_mode: Noneinclude_tokens_per_second: Falseinclude_num_input_tokens_seen: Falseneftune_noise_alpha: Noneoptim_target_modules: Nonebatch_eval_metrics: Falseeval_on_start: Falseuse_liger_kernel: Falseliger_kernel_config: Noneeval_use_gather_object: Falseaverage_tokens_across_devices: Falseprompts: Nonebatch_sampler: no_duplicatesmulti_dataset_batch_sampler: proportionalrouter_mapping: {}learning_rate_mapping: {}| Epoch | Step | Training Loss | Validation Loss |
|---|---|---|---|
| 0.6667 | 100 | 8.4683 | 3.9621 |
1@inproceedings{reimers-2019-sentence-bert,
2 title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
3 author = "Reimers, Nils and Gurevych, Iryna",
4 booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
5 month = "11",
6 year = "2019",
7 publisher = "Association for Computational Linguistics",
8 url = "https://arxiv.org/abs/1908.10084",
9}1@article{10531646,
2 author={Huang, Xiang and Peng, Hao and Zou, Dongcheng and Liu, Zhiwei and Li, Jianxin and Liu, Kay and Wu, Jia and Su, Jianlin and Yu, Philip S.},
3 journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
4 title={CoSENT: Consistent Sentence Embedding via Similarity Ranking},
5 year={2024},
6 doi={10.1109/TASLP.2024.3402087}
7}