Good Papers

Showing papers from Indian Institute of Technology Bombay Show all papers

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Indian Institute of Technology, Indian Institute of Technology BIIT BombayAdversarial robustness

Adversarial Corpus Selection to Attack Subgraph Matching based Graph Retrieval

Ninad Gandhi, Mayukh Mondal, Brian S Mackwan, Soumen Chakrabarti and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Indian Institute of Technology, Indian Institute of Technology BIIT BombayAdversarial robustness

A Solver-Efficient Neural Adversarial Attack on Subgraph Matching Models

Ninad Gandhi, Mayukh Mondal, Brian S Mackwan, Soumen Chakrabarti and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026Indian Institute of Technology, Indian Institute of Technology BIndian Institute of Technology BDepartment of Chemistry and CentIIT BombayMolecules & drug discovery

Position: Machine Learning Models for Reaction Transition States Deserve Better

Atharva Tambat, Ankit Ghosh, Swastik Kumar, Raghavan B Sunoj and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026MITIndian Institute of Technology BGraph neural networks

Network Intervention by Polling Strategic Agents

Chenyu Zhang, Rohit Parasnis, Saurabh Amin

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Indian Institute of Technology, MicrosoftAalto University / IIT BombayIIT BombayMicrosoft Research Lab IndiaGraphs & LLMs

Active Corpus Selection for Training Subgraph Retrievers Using OOD Queries

Pritish Chakraborty, Aditya Singh, Indradyumna Roy, Lokesh N and 7 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
91%Must read
?Must readVote to see the score
NeurIPS 2026U MichiganIndian Institute of Technology BU Michigan - Ann ArborAI oversight & deception

SchemeArena: Factorized Stress Testing of Scheming in LLM Agents

SchemeArena introduces a 400-scenario benchmark and SCOUT monitor for factorized LLM agent scheming stress tests, finding explicit instrumental goals drive scheming most strongly and partial oversight can increase covert behavior.

Jie Ruan, Inderjeet Nair, Amy Liu, Muhammad Khalifa and 2 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 11 on Hugging Face · Code ★ 1

– ReadersNo votes yet
18/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 18 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 4/5