Search Results for author:
Found 48 papers, 26 papers with code
Alignment-Augmented Consistent Translation for Multilingual Open Information Extraction
Progress with supervised Open Information Extraction (OpenIE) has been primarily limited to English due to the scarcity of training data in other languages.
Ranked #1 on
Open Information Extraction
on OpenIE
A Data Bootstrapping Recipe for Low-Resource Multilingual Relation Classification
Data collection is challenging for Indian languages, because they are syntactically and morphologically diverse, as well as different from resource-rich languages like English.
Cost-Performance Optimization for Processing Low-Resource Language Tasks Using Commercial LLMs
As means to reduce the number of tokens processed by the LLM, we consider code-mixing, translation, and transliteration of LRLs to HRLs.
How to think step-by-step: A mechanistic understanding of chain-of-thought reasoning
Despite superior reasoning prowess demonstrated by Large Language Models (LLMs) with Chain-of-Thought (CoT) prompting, a lack of understanding prevails around the internal mechanisms of the models that facilitate CoT generation.
Graph Regularized Encoder Training for Extreme Classification
The paper notices that in these settings, it is much more effective to use graph data to regularize encoder training than to implement a GCN.
Frugal LMs Trained to Invoke Symbolic Solvers Achieve Parameter-Efficient Arithmetic Reasoning
In this paper, we start with the hypothesis that much smaller LMs, which are weak at multi-step reasoning, can achieve reasonable arithmetic reasoning if arithmetic word problems are posed as a formalize-then-solve task.
Ranked #11 on
Math Word Problem Solving
on SVAMP
(using extra training data)
CoRE-CoG: Conversational Recommendation of Entities using Constrained Generation
End-to-end conversational recommendation systems (CRS) generate responses by leveraging both dialog history and a knowledge base (KB).
CRUSH4SQL: Collective Retrieval Using Schema Hallucination For Text2SQL
Standard dense retrieval techniques are inadequate for schema subsetting of a large structured database, where the correct semantics of retrieval demands that we rank sets of schema elements rather than individual elements.
Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoning
Additionally, we show that DaSLaM is not limited by the solver's capabilities as a function of scale; e. g., solver LMs with diverse sizes give significant performance improvement with our solver-agnostic decomposition technique.
Ranked #6 on
Overall - Test
on JEEBench
(using extra training data)
Structured Case-based Reasoning for Inference-time Adaptation of Text-to-SQL parsers
To the best of our knowledge, we are the first to attempt inference-time adaptation of Text-to-SQL models, and harness trainable structured similarity between subqueries.
mOKB6: A Multilingual Open Knowledge Base Completion Benchmark
Automated completion of open knowledge bases (Open KBs), which are constructed from triples of the form (subject phrase, relation phrase, object phrase), obtained via open information extraction (Open IE) system, are useful for discovering novel facts that may not be directly present in the text.
Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection
We do not draw the concave function from a restricted family, but rather learn from data using a highly expressive neural network that implements a differentiable quadrature procedure.
Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks
A common consideration for scoring similarity is the maximum common subgraph (MCS) between the query and corpus graphs, usually counting the number of common edges (i. e., MCES).
TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs
Recent years have witnessed much interest in temporal reasoning over knowledge graphs (KG) for complex question answering (QA), but there remains a substantial gap in human capabilities.
Semi-supervised Stance Detection of Tweets Via Distant Network Supervision
Detecting and labeling stance in social media text is strongly motivated by hate speech detection, poll prediction, engagement forecasting, and concerted propaganda detection.
Multi-Row, Multi-Span Distant Supervision For Table+Text Question
Question answering (QA) over tables and linked text, also called TextTableQA, has witnessed significant research in recent years, as tables are often found embedded in documents along with related text.
A Data Bootstrapping Recipe for Low Resource Multilingual Relation Classification
Relation classification (sometimes called 'extraction') requires trustworthy datasets for fine-tuning large language models, as well as for evaluation.
Redesigning the Transformer Architecture with Insights from Multi-particle Dynamical Systems
The Transformer and its variants have been proven to be efficient sequence learners in many different domains.
Topic Transferable Table Question Answering
Weakly-supervised table question-answering(TableQA) models have achieved state-of-art performance by using pre-trained BERT transformer to jointly encoding a question and a table to produce structured query for the question.
Integrating Transductive And Inductive Embeddings Improves Link Prediction Accuracy
In recent years, inductive graph embedding models, \emph{viz.
AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industry
Recent advances in transformers have enabled Table Question Answering (Table QA) systems to achieve high accuracy and SOTA results on open domain datasets like WikiTableQuestions and WikiSQL.
Incomplete Gamma Integrals for Deep Cascade Prediction using Content, Network, and Exogenous Signals
Second, there is a measurable positive correlation between the novelty of the root content (with respect to a streaming external corpus) and the relative size of the resulting cascade.
Question Answering Over Temporal Knowledge Graphs
Temporal Knowledge Graphs (Temporal KGs) extend regular Knowledge Graphs by providing temporal scopes (start and end times) on each edge in the KG.
Ranked #5 on
Question Answering
on CronQuestions
Multilingual Knowledge Graph Completion with Joint Relation and Entity Alignment
Almost all of existing KGC research is applicable to only one KG at a time, and in one language only.
Ranked #2 on
Knowledge Graph Completion
on DBP-5L (Greek)
Select, Substitute, Search: A New Benchmark for Knowledge-Augmented Visual Question Answering
In response, we identify a key structural idiom in OKVQA , viz., S3 (select, substitute and search), and build a new data set and challenge around it.
Joint Autoregressive and Graph Models for Software and Developer Social Networks
This "social network of code" is rarely studied by social network researchers.
Adversarial Permutation Guided Node Representations for Link Prediction
Sequence encoders are more expressive, but are permutation sensitive by design.
OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction
This IGL based coordination analyzer helps our OpenIE system handle complicated coordination structures, while also establishing a new state of the art on the task of coordination analysis, with a 12. 3 pts improvement in F1 over previous analyzers.
Ranked #1 on
Open Information Extraction
on WiRe57
NLP Service APIs and Models for Efficient Registration of New Clients
Each client uses an unsupervised, corpus-based sketch to register to the service.
IMoJIE: Iterative Memory-Based Joint Open Information Extraction
While traditional systems for Open Information Extraction were statistical and rule-based, recently neural models have been introduced for the task.
Temporal Knowledge Base Completion: New Algorithms and Evaluation Protocols
Temporal knowledge bases associate relational (s, r, o) triples with a set of times (or a single time instant) when the relation is valid.
Ranked #1 on
Link Prediction
on Wikidata12k
Knowledge Base Completion: Baseline strikes back (Again)
Most existing methods train with a small number of negative samples for each positive instance in these datasets to save computational costs.
Scene Graph based Image Retrieval -- A case study on the CLEVR Dataset
With the prolification of multimodal interaction in various domains, recently there has been much interest in text based image retrieval in the computer vision community.
Differentially Private Link Prediction With Protected Connections
Link prediction (LP) algorithms propose to each node a ranked list of nodes that are currently non-neighbors, as the most likely candidates for future linkage.
A Deep Generative Model for Code-Switched Text
Code-switching, the interleaving of two or more languages within a sentence or discourse is pervasive in multilingual societies.
Improved Sentiment Detection via Label Transfer from Monolingual to Synthetic Code-Switched Text
Consequently, the best monolingual methods perform relatively poorly on code-switched text.
Topic Sensitive Attention on Generic Corpora Corrects Sense Bias in Pretrained Embeddings
Given a small corpus $\mathcal D_T$ pertaining to a limited set of focused topics, our goal is to train embeddings that accurately capture the sense of words in the topic in spite of the limited size of $\mathcal D_T$.
Complex Program Induction for Querying Knowledge Bases in the Absence of Gold Programs
On one of the hardest class of programs (comparative reasoning) with 5{--}10 steps, CIPITR outperforms NSM by a factor of 89 and memory networks by 9 times.
Multi-task Learning for Target-dependent Sentiment Classification
The auxiliary and main GRUs send their states to a different fully connected layer, trained for the main task.
GIRNet: Interleaved Multi-Task Recurrent State Sequence Models
A primary instance is also submitted to each auxiliary RNN, but their state sequences are gated and merged into a novel composite state sequence tailored to the primary inference task.
Type-Sensitive Knowledge Base Inference Without Explicit Type Supervision
State-of-the-art knowledge base completion (KBC) models predict a score for every known or unknown fact via a latent factorization over entity and relation embeddings.
Generalizing Across Domains via Cross-Gradient Training
We present CROSSGRAD, a method to use multi-domain training data to learn a classifier that generalizes to new domains.
Ranked #83 on
Domain Generalization
on PACS
Automated Early Leaderboard Generation From Comparative Tables
We propose several approaches to rank papers from these noisy 'match' outcomes.
Joint Matrix-Tensor Factorization for Knowledge Base Inference
If not, what characteristics of a dataset determine the performance of MF and TF models?
Discriminative Link Prediction using Local Links, Node Features and Community Structure
Apart from the new predictor, another contribution is a rigorous protocol for benchmarking and reporting LP algorithms, which reveals the regions of strengths and weaknesses of all the predictors studied here, and establishes the new proposal as the most robust.
