Rishab Bala

22 posts

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Rishab Bala

Rishab Bala

@Sub_RBala

PhD student @VT_CS

Corvallis, Oregon 가입일 Mart 2022
2.4K 팔로잉186 팔로워
Rishab Bala
Rishab Bala@Sub_RBala·
The 3 self-distillation papers seem to be extremely similar in the method and only differ in how the feedback is generated/incorporated. They are also only compared to SFT (known to be the weakest method), while incorporating feedback is also done with other PO methods. Not quite sure of the takeaways, but the improvements and continual learning settings look good!
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Thomas Kleine Buening
Thomas Kleine Buening@thomasklbg·
Deployed LLMs and users generate millions of conversations every day. These are full of useful learning signals, yet we don't use them for training. We introduce self-distillation for learning directly from user conversations – no rewards, no labels, no extra models.
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Hao Zhao
Hao Zhao@HaoZhao_AIRSUN·
What really drives paper acceptance? 🤔📄 We analyze the entire peer-review process (scores, rebuttals, reviewer behavior) and turn it into a predictive, interpretable system. 🚀 PaperDecision A large-scale benchmark + multi-agent framework for real peer review modeling. 📊 Key highlights • 82.44% accuracy on ICLR 2025 accept/reject prediction • Stable generalization across ICLR 2023–2025 • First benchmark spanning paper → reviews → rebuttals → decisions 🤖 Why multi-agent? Reviewer → Summarizer → Rebuttal Analyzer → Decision Agent This structured workflow significantly outperforms single-agent prediction. 📈 What actually matters • Avg reviewer score is king (+0.705) • Rebuttal success ≈ reviewer scores (+0.53) • One stubborn reviewer can kill a paper (−0.32) • Experts are harder to please • Surprisingly, shallow reviewers can help 🌐 Project page: paperdecision.netlify.app 💻 Code & data: github.com/PaperDecision/… If you care about peer review, meta-science, or LLM agents, this is for you. 🧠✨
Hao Zhao tweet media
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Rishab Bala
Rishab Bala@Sub_RBala·
@ryolu_ @cursor_ai Before all that can we get a way to remap autocompletes from tab to another button? And a way to get partial edits?
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Rishab Bala
Rishab Bala@Sub_RBala·
Really cool work. Can you share the difference in generation lengths between the parallel approach and and traditional AR models. Latency reduction with parallel thought makes sense, but without a comparison on the total number generated tokens the speedup/# parallel isnt useful. Maybe wall-clock time comparison makes more sense here?
Infini-AI-Lab@InfiniAILab

🔥 We introduce Multiverse, a new generative modeling framework for adaptive and lossless parallel generation. 🚀 Multiverse is the first open-source non-AR model to achieve AIME24 and AIME25 scores of 54% and 46% 🌐 Website: multiverse4fm.github.io 🧵 1/n

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Tu Vu
Tu Vu@tuvllms·
✨ New paper ✨ 🚨 Scaling test-time compute can lead to inverse or flattened scaling!! We introduce SealQA, a new challenge benchmark w/ questions that trigger conflicting, ambiguous, or unhelpful web search results. Key takeaways: ➡️ Frontier LLMs struggle on Seal-0 (SealQA’s core set): most chat models (incl. GPT-4.1 w/ browsing) achieve near-zero accuracy ➡️ Advanced reasoning models (e.g., DeepSeek-R1) can be highly vulnerable to noisy search results ➡️ More test-time compute does not yield reliable gains: o-series models often plateau or decline early ➡️ "Lost-in-the-middle" is less of an issue, but models still fail to reliably identify relevant docs amid distractors 📜: arxiv.org/abs/2506.01062 🤗: huggingface.co/datasets/vtllm… 🧵:👇
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Tim Dettmers
Tim Dettmers@Tim_Dettmers·
Catch my talk today "Lessons Learned from Successful PhD Students" where I will talk about the science of success in academia and what it means for your own research. 10:45am in the Mission City Ballroom mlsys.org/virtual/2025/i…
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Rishab Bala
Rishab Bala@Sub_RBala·
@ylongqi Hey Longqi, Im a Phd student at Virginia Tech working on multi task learning, model merging, and reasoning of LLMs. My CV is attached in my bio. Let me lnow if you’re interested.
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Longqi Yang
Longqi Yang@ylongqi·
Internship alert! We have an immediate part-time research intern opening at Microsoft’s Office of Applied Research to improve LLM reasoning. Please reach out if you or your students are interested!
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martin_casado
martin_casado@martin_casado·
Hey infra folks. We're standing up a new Discord server to discuss CS infra. If you want an invite DM me (reply and I'll follow). thanks!
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Alex Warstadt
Alex Warstadt@a_stadt·
I'm in need of NINE emergency reviews for ACL ARR. Over 1/3 of my reviewers are nonresponsive, I think that's a personal record 🙃 Please let me know if you can take on some of these!!
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Rishab Bala
Rishab Bala@Sub_RBala·
@soumyabrata_pal Hey @soumyabrata_pal, I'm interested and I have experience in theory and experiments. I'm not able to send a DM, but my resume and website are in my bio. Please let me know if you'd be interested
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Soumyabrata Pal
Soumyabrata Pal@soumyabrata_pal·
Looking for PhD interns (2025) at Adobe Research (Bangalore) who are interested in either A) ML Theory/Applied Statistics or B) some aspect of LLM Optimization. Please reach out if interested. Recent papers: 1) arxiv.org/abs/2410.20041 2)arxiv.org/abs/2410.12513
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Rishab Bala
Rishab Bala@Sub_RBala·
@guohao_li @CamelAIOrg Hey Guohao, I’m interested in applying. You can checkout my resume and profile in my bio. If you’re interested let me know
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Guohao Li 🐫
Guohao Li 🐫@guohao_li·
Hiring a Research Intern at @CamelAIOrg 🐫! This role involves working on data generation and multi-agent systems, contributing directly to @CamelAIOrg’s projects. Expected outcomes include open-source contributions and submission of research findings to a top-tier ML conference. Preferred duration is 6 months or longer, with a minimum commitment of 3 months. London based or remote. 📧 If this role interests you, please send your CV and a few paragraphs demonstrating your motivations to hr@eigent.ai. RT is very much appreciated 🙏 eigent-ai.notion.site/Research-Inter…
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Rishab Bala
Rishab Bala@Sub_RBala·
@Francis_YAO_ @rasbt Starting my PhD and in a similar position. How do you stay up to date and find good ideas without reading papers?
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Yao Fu
Yao Fu@Francis_YAO_·
@rasbt I’ll vote for your solution.
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Yao Fu
Yao Fu@Francis_YAO_·
Looking back, the largest problem of my own phd journey is reading too many papers and writing too few codes 😮‍💨
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Huazheng Wang
Huazheng Wang@huazheng_wang·
Are combinatorial bandits vulnerable to reward poisoning attacks? In our #ICML2024 paper, we characterize the attackability condition and show some CMAB instances are intrinsically robust. Surprisingly, the attackability is different between white-box and black-box attacks.(1/2)
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Huazheng Wang
Huazheng Wang@huazheng_wang·
At #NeurIPS2023 till Saturday. Happy to share our work "Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective". Check the poster at Session 5 Thu 10:45 - 12:45 CST. Looking forward to discussing RL, recommendation, ranking with friends and colleagues! (1/3)
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