Publications (89)
CoCoA: Confidence and Context-Aware Adaptive Decoding for Resolving Knowledge Conflicts in Large Language Models
Anant Khandelwal, Manish Gupta, Puneet Agrawal
Faithful generation in large language models (LLMs) is challenged by knowledge conflicts between parametric memory and external context. Existing contrastive decoding methods tuned…
SUMMIR: A Hallucination-Aware Framework for Ranking Sports Insights from LLMs
Nitish Kumar, Sannu Kumar, S Akash +3
With the rapid proliferation of online sports journalism, extracting meaningful pre-game and post-game insights from articles is essential for enhancing user engagement and compreh…
Visio-Linguistic Brain Encoding
Subba Reddy Oota, Jashn Arora, Vijay Rowtula +2
Enabling effective brain-computer interfaces requires understanding how the human brain encodes stimuli across modalities such as visual, language (or text), etc. Brain encoding ai…
Unity in Diversity: Learning Distributed Heterogeneous Sentence Representation for Extractive Summarization
Abhishek Kumar Singh, Manish Gupta, Vasudeva Varma
Automated multi-document extractive text summarization is a widely studied research problem in the field of natural language understanding. Such extractive mechanisms compute in so…
Under the Shadow of Sunshine: Characterizing Spam Campaigns Abusing Phone Numbers Across Online Social Networks
Srishti Gupta, Dhruv Kuchhal, Payas Gupta +3
Cybercriminals abuse Online Social Networks (OSNs) to lure victims into a variety of spam. Among different spam types, a less explored area is OSN abuse that leverages the telephon…
XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource Languages
Dhaval Taunk, Shivprasad Sagare, Anupam Patil +3
Lack of encyclopedic text contributors, especially on Wikipedia, makes automated text generation for low resource (LR) languages a critical problem. Existing work on Wikipedia text…
Deep Learning for Hate Speech Detection in Tweets
Pinkesh Badjatiya, Shashank Gupta, Manish Gupta +1
Hate speech detection on Twitter is critical for applications like controversial event extraction, building AI chatterbots, content recommendation, and sentiment analysis. We defin…
STWalk: Learning Trajectory Representations in Temporal Graphs
Supriya Pandhre, Himangi Mittal, Manish Gupta +1
Analyzing the temporal behavior of nodes in time-varying graphs is useful for many applications such as targeted advertising, community evolution and outlier detection. In this pap…
NEWSKVQA: Knowledge-Aware News Video Question Answering
Pranay Gupta, Manish Gupta
Answering questions in the context of videos can be helpful in video indexing, video retrieval systems, video summarization, learning management systems and surveillance video anal…
Molecular Dynamics Simulation of Bubble Nucleation in Hydrophilic Nanochannels by Surface Heating
Manish Gupta, Shalabh C. Maroo
Bubble nucleation in liquid confined in nanochannel is studied using molecular dynamics simulations and compared against nucleation in the liquid over smooth (i.e. without confinem…
Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey)
Subba Reddy Oota, Zijiao Chen, Manish Gupta +4
Can artificial intelligence unlock the secrets of the human brain? How do the inner mechanisms of deep learning models relate to our neural circuits? Is it possible to enhance AI b…
ReFeR: Improving Evaluation and Reasoning through Hierarchy of Models
Yaswanth Narsupalli, Abhranil Chandra, Sreevatsa Muppirala +2
Assessing the quality of outputs generated by generative models, such as large language models and vision language models, presents notable challenges. Traditional methods for eval…
Improving Tweet Representations using Temporal and User Context
Ganesh J, Manish Gupta, Vasudeva Varma
In this work we propose a novel representation learning model which computes semantic representations for tweets accurately. Our model systematically exploits the chronologically a…
How does longer temporal context enhance multimodal narrative video processing in the brain?
Prachi Jindal, Anant Khandelwal, Manish Gupta +3
Understanding how humans and artificial intelligence systems process complex narrative videos is a fundamental challenge at the intersection of neuroscience and machine learning. T…
Frugal Prompting for Dialog Models
Bishal Santra, Sakya Basak, Abhinandan De +2
The use of large language models (LLMs) in natural language processing (NLP) tasks is rapidly increasing, leading to changes in how researchers approach problems in the field. To f…
Transformer Models for Text Coherence Assessment
Tushar Abhishek, Daksh Rawat, Manish Gupta +1
Coherence is an important aspect of text quality and is crucial for ensuring its readability. It is essential desirable for outputs from text generation systems like summarization,…
FIND: Toward Multimodal Financial Reasoning and Question Answering for Indic Languages
Sarmistha Das, Vaibhav Vishal, Syed Ibrahim Ahmad +2
Financial decision-making in multilingual settings demands accurate numerical reasoning grounded in diverse modalities, yet existing benchmarks largely overlook this high-stakes, r…
TripCraft: A Benchmark for Spatio-Temporally Fine Grained Travel Planning
Soumyabrata Chaudhuri, Pranav Purkar, Ritwik Raghav +4
Recent advancements in probing Large Language Models (LLMs) have explored their latent potential as personalized travel planning agents, yet existing benchmarks remain limited in r…
Linguistic properties and model scale in brain encoding: from small to compressed language models
Subba Reddy Oota, Vijay Rowtula, Satya Sai Srinath Namburi +5
Recent work has shown that scaling large language models (LLMs) improves their alignment with human brain activity, yet it remains unclear what drives these gains and which represe…
Unsupervised Language agnostic WER Standardization
Satarupa Guha, Rahul Ambavat, Ankur Gupta +2
Word error rate (WER) is a standard metric for the evaluation of Automated Speech Recognition (ASR) systems. However, WER fails to provide a fair evaluation of human perceived qual…
Disjoining Pressure of Water in Nanochannels
An Zou, Sajag Poudel, Manish Gupta +1
Experiments of water wicking in 1D silicon-dioxide nanochannels of heights 59 nm, 87 nm, 124 nm and 1015 nm are used to estimate the disjoining pressure of water which was found to…
Hybrid MemNet for Extractive Summarization
Abhishek Kumar Singh, Manish Gupta, Vasudeva Varma
Extractive text summarization has been an extensive research problem in the field of natural language understanding. While the conventional approaches rely mostly on manually compi…
Trie-NLG: Trie Context Augmentation to Improve Personalized Query Auto-Completion for Short and Unseen Prefixes
Kaushal Kumar Maurya, Maunendra Sankar Desarkar, Manish Gupta +1
Query auto-completion (QAC) aims to suggest plausible completions for a given query prefix. Traditionally, QAC systems have leveraged tries curated from historical query logs to su…
HateMM: A Multi-Modal Dataset for Hate Video Classification
Mithun Das, Rohit Raj, Punyajoy Saha +3
Hate speech has become one of the most significant issues in modern society, having implications in both the online and the offline world. Due to this, hate speech research has rec…
In Agents We Trust, but Who Do Agents Trust? Latent Source Preferences Steer LLM Generations
Mohammad Aflah Khan, Mahsa Amani, Soumi Das +5
Agents based on Large Language Models (LLMs) are increasingly being deployed as interfaces to information on online platforms. These agents filter, prioritize, and synthesize infor…
Cross-view Brain Decoding
Subba Reddy Oota, Jashn Arora, Manish Gupta +1
How the brain captures the meaning of linguistic stimuli across multiple views is still a critical open question in neuroscience. Consider three different views of the concept apar…
Curriculum Learning for Cross-Lingual Data-to-Text Generation With Noisy Data
Kancharla Aditya Hari, Manish Gupta, Vasudeva Varma
Curriculum learning has been used to improve the quality of text generation systems by ordering the training samples according to a particular schedule in various tasks. In the con…
Elites Tweet? Characterizing the Twitter Verified User Network
Indraneil Paul, Abhinav Khattar, Ponnurangam Kumaraguru +2
Social network and publishing platforms, such as Twitter, support the concept of verification. Verified accounts are deemed worthy of platform-wide public interest and are separate…
A Deep Multi-Modal Method for Patient Wound Healing Assessment
Subba Reddy Oota, Vijay Rowtula, Shahid Mohammed +3
Hospitalization of patients is one of the major factors for high wound care costs. Most patients do not acquire a wound which needs immediate hospitalization. However, due to facto…
SCULPT: Systematic Tuning of Long Prompts
Shanu Kumar, Akhila Yesantarao Venkata, Shubhanshu Khandelwal +3
Prompt optimization is essential for effective utilization of large language models (LLMs) across diverse tasks. While existing optimization methods are effective in optimizing sho…
Summaformers @ LaySumm 20, LongSumm 20
Sayar Ghosh Roy, Nikhil Pinnaparaju, Risubh Jain +2
Automatic text summarization has been widely studied as an important task in natural language processing. Traditionally, various feature engineering and machine learning based syst…
Multi-label Categorization of Accounts of Sexism using a Neural Framework
Pulkit Parikh, Harika Abburi, Pinkesh Badjatiya +4
Sexism, an injustice that subjects women and girls to enormous suffering, manifests in blatant as well as subtle ways. In the wake of growing documentation of experiences of sexism…
Composite Sketch+Text Queries for Retrieving Objects with Elusive Names and Complex Interactions
Prajwal Gatti, Kshitij Parikh, Dhriti Prasanna Paul +2
Non-native speakers with limited vocabulary often struggle to name specific objects despite being able to visualize them, e.g., people outside Australia searching for numbats. Furt…
Discovering Multiple Design Approaches in Programming Assignment Submissions
Nikhila KN, Sujit Kumar Chakrabarti, Manish Gupta
In this paper, we present a novel approach of automated evaluation of programming assignments~(AEPA) the highlight of which is that it automatically identifies multiple solution ap…
Multilingual Bias Detection and Mitigation for Indian Languages
Ankita Maity, Anubhav Sharma, Rudra Dhar +3
Lack of diverse perspectives causes neutrality bias in Wikipedia content leading to millions of worldwide readers getting exposed by potentially inaccurate information. Hence, neut…
Fractional Rotation, Full Potential? Investigating Performance and Convergence of Partial RoPE
Mohammad Aflah Khan, Krishna P. Gummadi, Manish Gupta +1
Rotary Positional Embedding (RoPE) is a common choice in transformer architectures for encoding relative positional information. Although earlier work has examined omitting RoPE in…
Multi-modal brain encoding models for multi-modal stimuli
Subba Reddy Oota, Khushbu Pahwa, Mounika Marreddy +3
Despite participants engaging in unimodal stimuli, such as watching images or silent videos, recent work has demonstrated that multi-modal Transformer models can predict visual bra…
Chat-Ghosting: A Comparative Study of Methods for Auto-Completion in Dialog Systems
Sandeep Mishra, Anubhab Mandal, Bishal Santra +3
Ghosting, the ability to predict a user's intended text input for inline query auto-completion, is an invaluable feature for modern search engines and chat interfaces, greatly enha…
TweetBoost: Influence of Social Media on NFT Valuation
Arnav Kapoor, Dipanwita Guhathakurta, Mehul Mathur +3
NFT or Non-Fungible Token is a token that certifies a digital asset to be unique. A wide range of assets including, digital art, music, tweets, memes, are being sold as NFTs. NFT-r…
Text2Arch: A Dataset for Generating Scientific Architecture Diagrams from Natural Language Descriptions
Shivank Garg, Sankalp Mittal, Manish Gupta
Communicating complex system designs or scientific processes through text alone is inefficient and prone to ambiguity. A system that automatically generates scientific architecture…
When Words Can't Capture It All: Towards Video-Based User Complaint Text Generation with Multimodal Video Complaint Dataset
Sarmistha Das, R E Zera Marveen Lyngkhoi, Kirtan Jain +3
While there exists a lot of work on explainable complaint mining, articulating user concerns through text or video remains a significant challenge, often leaving issues unresolved.…
Entropy-driven decision-making dynamics sheds light on the emergence of the "paradox of choice"
Manish Gupta, Arnab Barua, Haralampos Hatzikirou
Decision making is the cognitive process of selecting a course of action among multiple alternatives. As the decision maker belongs to a complex microenvironment (which contains mu…
Syntactic Structure Processing in the Brain while Listening
Subba Reddy Oota, Mounika Marreddy, Manish Gupta +1
Syntactic parsing is the task of assigning a syntactic structure to a sentence. There are two popular syntactic parsing methods: constituency and dependency parsing. Recent works h…
Answer Mining from a Pool of Images: Towards Retrieval-Based Visual Question Answering
Abhirama Subramanyam Penamakuri, Manish Gupta, Mithun Das Gupta +1
We study visual question answering in a setting where the answer has to be mined from a pool of relevant and irrelevant images given as a context. For such a setting, a model must…
Should I visit this place? Inclusion and Exclusion Phrase Mining from Reviews
Omkar Gurjar, Manish Gupta
Although several automatic itinerary generation services have made travel planning easy, often times travellers find themselves in unique situations where they cannot make the best…
Simultaneous Inference of User Representations and Trust
Shashank Gupta, Pulkit Parikh, Manish Gupta +1
Inferring trust relations between social media users is critical for a number of applications wherein users seek credible information. The fact that available trust relations are s…
CRAFT: Cost-aware Refinement And Front-aware Tuning of Prompts
Shanu Kumar, Shubhanshu Khandelwal, Akhila Yesantarao Venkata +3
Prompts tuned for accuracy often grow long, raising inference cost on every model call. The best accuracy-cost trade-off depends on the task and the budget, so prompt optimization…
USDC: A Dataset of ser tance and ogmatism in Long onversations
Mounika Marreddy, Subba Reddy Oota, Venkata Charan Chinni +2
Analyzing user opinion changes in long conversation threads is extremely critical for applications like enhanced personalization, market research, political campaigns, customer ser…
ECIS-VQG: Generation of Entity-centric Information-seeking Questions from Videos
Arpan Phukan, Manish Gupta, Asif Ekbal
Previous studies on question generation from videos have mostly focused on generating questions about common objects and attributes and hence are not entity-centric. In this work,…
What sets Verified Users apart? Insights, Analysis and Prediction of Verified Users on Twitter
Indraneil Paul, Abhinav Khattar, Shaan Chopra +2
Social network and publishing platforms, such as Twitter, support the concept of a secret proprietary verification process, for handles they deem worthy of platform-wide public int…
CORAL: Contextual Response Retrievability Loss Function for Training Dialog Generation Models
Bishal Santra, Ravi Ghadia, Manish Gupta +1
In the field of Natural Language Processing, there are many tasks that can be tackled effectively using the cross-entropy (CE) loss function. However, the task of dialog generation…
Compression of Deep Learning Models for Text: A Survey
Manish Gupta, Puneet Agrawal
In recent years, the fields of natural language processing (NLP) and information retrieval (IR) have made tremendous progress thanksto deep learning models like Recurrent Neural Ne…
Joint processing of linguistic properties in brains and language models
Subba Reddy Oota, Manish Gupta, Mariya Toneva
Language models have been shown to be very effective in predicting brain recordings of subjects experiencing complex language stimuli. For a deeper understanding of this alignment,…
Co-training for Extraction of Adverse Drug Reaction Mentions from Tweets
Shashank Gupta, Manish Gupta, Vasudeva Varma +3
Adverse drug reactions (ADRs) are one of the leading causes of mortality in health care. Current ADR surveillance systems are often associated with a substantial time lag before su…
Interpretation of Semantic Tweet Representations
J Ganesh, Manish Gupta, Vasudeva Varma
Research in analysis of microblogging platforms is experiencing a renewed surge with a large number of works applying representation learning models for applications like sentiment…
IndicSentEval: How Effectively do Multilingual Transformer Models encode Linguistic Properties for Indic Languages?
Akhilesh Aravapalli, Mounika Marreddy, Radhika Mamidi +2
Transformer-based models have revolutionized the field of natural language processing. To understand why they perform so well and to assess their reliability, several studies have…
Multi-Task Learning for Extraction of Adverse Drug Reaction Mentions from Tweets
Shashank Gupta, Manish Gupta, Vasudeva Varma +3
Adverse drug reactions (ADRs) are one of the leading causes of mortality in health care. Current ADR surveillance systems are often associated with a substantial time lag before su…
Attention-based Neural Text Segmentation
Pinkesh Badjatiya, Litton J Kurisinkel, Manish Gupta +1
Text segmentation plays an important role in various Natural Language Processing (NLP) tasks like summarization, context understanding, document indexing and document noise removal…
DNA-based chemical compiler
Shalin Shah, Manish Gupta
Marcello, in 1997, formally proved that chemical kinetics can make a universal computer i.e they can replicate any digital circuit. Recently, Soloveichik et al. showed that chemica…
Improving search relevance of Azure Cognitive Search by Bayesian optimization
Nitin Agarwal, Ashish Kumar, Kiran R +2
Azure Cognitive Search (ACS) has emerged as a major contender in "Search as a Service" cloud products in recent years. However, one of the major challenges for ACS users is to impr…
"Subverting the Jewtocracy": Online Antisemitism Detection Using Multimodal Deep Learning
Mohit Chandra, Dheeraj Pailla, Himanshu Bhatia +4
The exponential rise of online social media has enabled the creation, distribution, and consumption of information at an unprecedented rate. However, it has also led to the burgeon…
DocQAC: Adaptive Trie-Guided Decoding for Effective In-Document Query Auto-Completion
Rahul Mehta, Kavin R, Indrajit Pal +3
Query auto-completion (QAC) has been widely studied in the context of web search, yet remains underexplored for in-document search, which we term DocQAC. DocQAC aims to enhance sea…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
Inductive Framework for Multi-Aspect Streaming Tensor Completion with Side Information
Madhav Nimishakavi, Bamdev Mishra, Manish Gupta +1
Low rank tensor completion is a well studied problem and has applications in various fields. However, in many real world applications the data is dynamic, i.e., new data arrives at…
Assess and Prompt: A Generative RL Framework for Improving Engagement in Online Mental Health Communities
Bhagesh Gaur, Karan Gupta, Aseem Srivastava +2
Online Mental Health Communities (OMHCs) provide crucial peer and expert support, yet many posts remain unanswered due to missing support attributes that signal the need for help.…
Task-conditioned probing of instruction-tuned multimodal LLMs: Region-specific brain alignment patterns under naturalistic stimuli
Subba Reddy Oota, Khushbu Pahwa, Prachi Jindal +5
Recent voxel-wise multimodal brain encoding studies have shown that multimodal large language models (MLLMs) exhibit a higher degree of brain alignment compared to unimodal models.…
Router-Suggest: Dynamic Routing for Multimodal Auto-Completion in Visually-Grounded Dialogs
Sandeep Mishra, Devichand Budagam, Anubhab Mandal +3
Real-time multimodal auto-completion is essential for digital assistants, chatbots, design tools, and healthcare consultations, where user inputs rely on shared visual context. We…
XF2T: Cross-lingual Fact-to-Text Generation for Low-Resource Languages
Shivprasad Sagare, Tushar Abhishek, Bhavyajeet Singh +3
Multiple business scenarios require an automated generation of descriptive human-readable text from structured input data. Hence, fact-to-text generation systems have been develope…
Representation Learning for Conversational Data using Discourse Mutual Information Maximization
Bishal Santra, Sumegh Roychowdhury, Aishik Mandal +4
Although many pretrained models exist for text or images, there have been relatively fewer attempts to train representations specifically for dialog understanding. Prior works usua…
Cascade Markov Decision Processes: Theory and Applications
Manish Gupta
This paper considers the optimal control of time varying continuous time Markov chains whose transition rates are themselves Markov processes. In one set of problems the solution o…
Neural models for Factual Inconsistency Classification with Explanations
Tathagata Raha, Mukund Choudhary, Abhinav Menon +4
Factual consistency is one of the most important requirements when editing high quality documents. It is extremely important for automatic text generation systems like summarizatio…
DP-KB: Data Programming with Knowledge Bases Improves Transformer Fine Tuning for Answer Sentence Selection
Nic Jedema, Thuy Vu, Manish Gupta +1
While transformers demonstrate impressive performance on many knowledge intensive (KI) tasks, their ability to serve as implicit knowledge bases (KBs) remains limited, as shown on…
PatentLMM: Large Multimodal Model for Generating Descriptions for Patent Figures
Shreya Shukla, Nakul Sharma, Manish Gupta +1
Writing comprehensive and accurate descriptions of technical drawings in patent documents is crucial to effective knowledge sharing and enabling the replication and protection of i…
Interpreting the Syntactic and Social Elements of the Tweet Representations via Elementary Property Prediction Tasks
J Ganesh, Manish Gupta, Vasudeva Varma
Research in social media analysis is experiencing a recent surge with a large number of works applying representation learning models to solve high-level syntactico-semantic tasks…
AbuseAnalyzer: Abuse Detection, Severity and Target Prediction for Gab Posts
Mohit Chandra, Ashwin Pathak, Eesha Dutta +4
While extensive popularity of online social media platforms has made information dissemination faster, it has also resulted in widespread online abuse of different types like hate…
LoRA on the Go: Instance-level Dynamic LoRA Selection and Merging
Seungeon Lee, Soumi Das, Manish Gupta +1
Low-Rank Adaptation (LoRA) has emerged as a parameter-efficient approach for fine-tuning large language models. However, conventional LoRA adapters are typically trained for a sing…
Stereotypical Bias Removal for Hate Speech Detection Task using Knowledge-based Generalizations
Pinkesh Badjatiya, Manish Gupta, Vasudeva Varma
With the ever-increasing cases of hate spread on social media platforms, it is critical to design abuse detection mechanisms to proactively avoid and control such incidents. While…
Brain alignment of reasoning and action representations from vision-language and action models during naturalistic gameplay
Subba Reddy Oota, Anant Khandelwal, Khushbu Pahwa +4
Understanding how humans and artificial intelligence systems predict and plan by interacting with their environment is a fundamental challenge at the intersection of neuroscience a…
Neural Language Taskonomy: Which NLP Tasks are the most Predictive of fMRI Brain Activity?
Subba Reddy Oota, Jashn Arora, Veeral Agarwal +3
Several popular Transformer based language models have been found to be successful for text-driven brain encoding. However, existing literature leverages only pretrained text Trans…
Aligning Moments in Time using Video Queries
Yogesh Kumar, Uday Agarwal, Manish Gupta +1
Video-to-video moment retrieval (Vid2VidMR) is the task of localizing unseen events or moments in a target video using a query video. This task poses several challenges, such as th…
Robust outlier detection by de-biasing VAE likelihoods
Kushal Chauhan, Barath Mohan U, Pradeep Shenoy +2
Deep networks often make confident, yet, incorrect, predictions when tested with outlier data that is far removed from their training distributions. Likelihoods computed by deep ge…
Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain)
Subba Reddy Oota, Akshett Jindal, Ishani Mondal +6
Transformer-based language models, though not explicitly trained to mimic brain recordings, have demonstrated surprising alignment with brain activity. Progress in these models-thr…
Read the Trace, Steer the Path: Trajectory-Aware Reinforcement Learning for Diffusion Language Models
Anant Khandelwal, Manish Gupta
Diffusion large language models (dLLMs) generate responses by iteratively unmasking and revising many positions in parallel. This process leaves a rich denoising trace depicting wh…
HistoryBankQA: Multilingual Temporal Question Answering on Historical Events
Biswadip Mandal, Anant Khandelwal, Manish Gupta
Temporal reasoning about historical events is a critical skill for NLP tasks like event extraction, historical entity linking, temporal question answering, timeline summarization,…
On Robustness of Finetuned Transformer-based NLP Models
Pavan Kalyan Reddy Neerudu, Subba Reddy Oota, Mounika Marreddy +2
Transformer-based pretrained models like BERT, GPT-2 and T5 have been finetuned for a large number of natural language processing (NLP) tasks, and have been shown to be very effect…
Community-based Outlier Detection for Edge-attributed Graphs
Supriya Pandhre, Manish Gupta, Vineeth N Balasubramanian
The study of networks has emerged in diverse disciplines as a means of analyzing complex relationship data. Beyond graph analysis tasks like graph query processing, link analysis,…
Towards Proactively Forecasting Sentence-Specific Information Popularity within Online News Documents
Sayar Ghosh Roy, Anshul Padhi, Risubh Jain +2
Multiple studies have focused on predicting the prospective popularity of an online document as a whole, without paying attention to the contributions of its individual parts. We i…
XAlign: Cross-lingual Fact-to-Text Alignment and Generation for Low-Resource Languages
Tushar Abhishek, Shivprasad Sagare, Bhavyajeet Singh +3
Multiple critical scenarios (like Wikipedia text generation given English Infoboxes) need automated generation of descriptive text in low resource (LR) languages from English fact…
TripTide: A Benchmark for Adaptive Travel Planning under Disruptions
Priyanshu Karmakar, Soumyabrata Chaudhuri, Shubhojit Mallick +3
Recent efforts like TripCraft and TravelPlanner have advanced the use of Large Language Models ( LLMs) for personalized, constraint aware travel itinerary generation. Yet, real tra…