Update README.md

README.md

@@ -8,68 +8,79 @@ tags:
 - loss:ContrastiveLoss
 base_model: sentence-transformers/all-mpnet-base-v2
 widget:
-- source_sentence: 'Background: The study addresses the need for effective tools that
-    allow both novice and expert users to analyze the diversity of news coverage about
-    events. It highlights the importance of tailoring the interface to accommodate
-    non-expert users while also considering the insights of journalism-savvy users,
-    indicating a gap in existing systems that cater to varying levels of expertise
-    in news analysis.
-
-    Contribution: Combine ''a coordinated visualization interface tailored for visualization
-    non-expert users'' and '
+- source_sentence: >-
+    Background: The study addresses the need for effective tools that allow both
+    novice and expert users to analyze the diversity of news coverage about
+    events. It highlights the importance of tailoring the interface to
+    accommodate non-expert users while also considering the insights of
+    journalism-savvy users, indicating a gap in existing systems that cater to
+    varying levels of expertise in news analysis.
+
+    Contribution: Combine 'a coordinated visualization interface tailored for
+    visualization non-expert users' and 
   sentences:
   - a method considering lexical relationships
   - cross-modality self-supervised learning via masked visual language modeling
   - cognitive models of chaining
-- source_sentence: 'Background: Existing methods for anomaly detection on dynamic
-    graphs struggle with capturing complex time information in graph structures and
-    generating effective negative samples for unsupervised learning. These challenges
-    highlight the need for improved methodologies that can address the limitations
-    of current approaches in this field.
-
-    Contribution: Combine ''a message-passing framework'' and '
+- source_sentence: >-
+    Background: Existing methods for anomaly detection on dynamic graphs
+    struggle with capturing complex time information in graph structures and
+    generating effective negative samples for unsupervised learning. These
+    challenges highlight the need for improved methodologies that can address
+    the limitations of current approaches in this field.
+
+    Contribution: Combine 'a message-passing framework' and 
   sentences:
   - the grouping task
   - a forecaster
   - the optimisation algorithm producing the learnable model
-- source_sentence: 'Background: The accuracy of pixel flows is crucial for achieving
-    high-quality video enhancement, yet most prior works focus on estimating dense
-    flows that are generally less robust and computationally expensive. This highlights
-    a gap in existing methodologies that fail to prioritize accuracy over density,
-    necessitating a more efficient approach to flow estimation for video enhancement
-    tasks.
-
-    Contribution: Combine ''sparse point cloud data'' and '
+- source_sentence: >-
+    Background: The accuracy of pixel flows is crucial for achieving
+    high-quality video enhancement, yet most prior works focus on estimating
+    dense flows that are generally less robust and computationally expensive.
+    This highlights a gap in existing methodologies that fail to prioritize
+    accuracy over density, necessitating a more efficient approach to flow
+    estimation for video enhancement tasks.
+
+    Contribution: Combine 'sparse point cloud data' and 
   sentences:
   - a deep CNN
   - a reinforcement learning view of the dialog generation task
   - graphical models
-- source_sentence: 'Background: The optimal robot assembly planning problem is challenging
-    due to the necessity of finding the optimal solution amongst an exponentially
-    vast number of possible plans while satisfying a selection of constraints. Traditional
-    heuristic methods are limited as they are specific to a given objective structure
-    or set of problem parameters, indicating a need for more versatile and effective
-    approaches.
-
-    Contribution: ''pos[e] assembly sequencing'' inspired by '
+- source_sentence: >-
+    Background: The optimal robot assembly planning problem is challenging due
+    to the necessity of finding the optimal solution amongst an exponentially
+    vast number of possible plans while satisfying a selection of constraints.
+    Traditional heuristic methods are limited as they are specific to a given
+    objective structure or set of problem parameters, indicating a need for more
+    versatile and effective approaches.
+
+    Contribution: 'pos[e] assembly sequencing' inspired by 
   sentences:
   - 3D geometric neural field representation
   - prompt learning
   - gestures
-- source_sentence: 'Background: Patients find it difficult to use dexterous prosthetic
-    hands without a suitable control system, highlighting a need for improved grasp
-    performance and ease of operation. Existing methods may not adequately address
-    the challenges faced by users, particularly those with inferior myoelectric signals,
-    in effectively controlling prosthetic devices.
-
-    Contribution: Combine ''myoelectric signal'' and '
+- source_sentence: >-
+    Background: Patients find it difficult to use dexterous prosthetic hands
+    without a suitable control system, highlighting a need for improved grasp
+    performance and ease of operation. Existing methods may not adequately
+    address the challenges faced by users, particularly those with inferior
+    myoelectric signals, in effectively controlling prosthetic devices.
+
+    Contribution: Combine 'myoelectric signal' and 
   sentences:
-  - a unified framework for collaborative decoding between large and small language
-    models (Large Language Models and small language models)
+  - >-
+    a unified framework for collaborative decoding between large and small
+    language models (Large Language Models and small language models)
   - image understanding
   - joint biomedical entity linking and event extraction
 pipeline_tag: sentence-similarity
 library_name: sentence-transformers
+license: mit
+datasets:
+- noystl/Recombination-Pred
+language:
+- en
 ---
 
 # SentenceTransformer based on sentence-transformers/all-mpnet-base-v2