Good Papers

Showing papers from Texas Tech University Show all papers

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Texas TechPhysics-informed ML & PDEs

Stop Quantum Machine Learning; do AI-for-Quantum instead

ziqing Guo, Ziwen Pan

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · 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 2026Texas TechU Texas at El PasoRepresentation & contrastive learning

A Deep Learning Framework for Scalar-on-Function Models

Ruiqi Liu, Suneel Babu Chatla

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · 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 2026U TorontoU Massachusetts BostonIIT MadrasSan Jose StateU AlbertaDeep RL

Reinforcement Learning Agents Are Swimmers

Juan Rojas, Jacob Adamczyk, Abhishek Naik, Volodymyr Makarenko and 5 more

Sydney Poster Session 4, Wed, Dec 9, 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
86%Must read
?Must readVote to see the score
NeurIPS 2026OralTexas TechExploration

Emergence of Physical Intelligence via Controllable Information Production

Controllable Information Production grounds intrinsic motivation in dynamics and control, unifying them to measure controllable information production and outperforming prior methods on robot tasks.

Tristan Shah, Stas Tiomkin

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
14/20 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: 14 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 1/5
80%Must read
?Must readVote to see the score
NeurIPS 2026Umass AmherstU Massachusetts at AmherstTexas TechU ConnecticutU Massachusetts, AmherstRL for LLMs

RICE-PO: Turning Retrieval Interactions into Credit Signals for Reasoning Agents

RICE-PO turns retrieval interactions into localized credit signals to train reasoning agents, outperforming RL baselines on BRIGHT and BEIR.

mingchen li, Hansi Zeng, Zhuo Qian, Jiatan Huang and 3 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
12/20 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: 12 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 0/5